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Shifting sands Explaining and predicting phase shifts by dissident organizations
Abstract
Why does a dissident group go through phases of violence and nonviolence? Many studies of states and dissidents examine related issues by focusing on structural or rarely changing factors. In contrast, some more recent work focuses on dynamic interaction of participants. We suggest forecasting state–dissident interaction using insights from this dynamic approach while also incorporating structural factors. We explore this question by offering new data on the behavior of groups and governments collected using automated natural language processing techniques. These data provide information on who is doing what to whom at a directed-dyadic level. We also collected new data on the attitudes or sentiment of the masses using novel automated techniques. Since obtaining valid and reliable time-series public opinion data on mass attitudes towards a dissident group is extremely difficult, we have created automated sentiment data by scraping publicly available information written by members of the population and aggregating this information to create a pollof opinion at a discrete time period. We model the violence and nonviolence perpetrated by two groups: the Tamil Tigers in Sri Lanka and the Moro Islamic Liberation Front in the Philippines. We find encouraging results for predicting future phase shifts in violence when accounting for behaviors modeled with our data as opposed to models based solely on structural factors.
... The study and prediction of social unrest has primarily been done through the study of social media messaging (example: Twitter and Facebook) using various natural language processing (NLP) techniques [47,42,35,52]. While there has been some research that use macro-structural data such as political, social, economic and demographic factors [44,55], grouping of related events are often done by human experts. In case of predictive models, it is often the subject matter experts that create profiles for a country or location. ...
... In SURGE, we use socioeconomic data collected from census data and infrastructure data collected from OpenStreetMap. The only other product that uses data related to the demographics is [55], as explained in Section 2.3.4. All projects other than EMBERS use data that is either related to specific type of event, for example [18] only uses data related to two sets of events, both related to the Black Lives Matter movement, and [55] only discuss the activities of two dissident groups. ...
... The only other product that uses data related to the demographics is [55], as explained in Section 2.3.4. All projects other than EMBERS use data that is either related to specific type of event, for example [18] only uses data related to two sets of events, both related to the Black Lives Matter movement, and [55] only discuss the activities of two dissident groups. SURGE on the other hand, uses data under eight unrest categories, identified by social scientists as relevant, and currently does not focus on the actors. ...
Social unrest such as appeals, protests, conflicts, fights and mass violence can result from a wide ranging of diverse factors making the analysis of causal relationships challenging, with high complexity and uncertainty. Unrest events can result in significant changes in a society ranging from new policies and regulations to regime change. Widespread unrest often arises through a process of feedback and cascading of a collection of past events over time, in regions that are close to each other. Understanding the dynamics of these social events and extrapolating their future growth will enable analysts to detect or forecast major societal events. The study and prediction of social unrest has primarily been done through case-studies and study of social media messaging using various natural language processing techniques. The grouping of related events is often done by subject matter experts that create profiles for countries or locations. We propose two approaches in understanding and modelling social unrest data: (1) spatio-temporal data clustering, and (2) agent-based modelling. We apply the clustering solution to real-world unrest events with socioeconomic and infrastructure factors. We also present a framework of an agent-based model where unrest events act as intelligent agents that continuously study their environment and perform actions. We run simulations of the agent-based model under varying conditions and evaluate the results in comparison to real-world data. Our results show the viability of our proposed solutions. Adviser: Leen-Kiat Soh and Ashok Samal
... There is evidence that fighting and other forms of political resistance are interdependent phenomena and even impact directly or indirectly similar conflict dynamics (White 1989). This leads scholars to investigate the interplay (Dudouet 2013;Shellman, Levey, and Young 2013) or trade-off (Chenoweth and Stephan 2011) between nonviolent and violent campaigns. We contribute to this literature by arguing that political behavior, short of fighting (e.g., demonstrations or strikes) in the context of ongoing civil conflict, can be the consequence of successful rebel organizations, which signal government weakness and enable widespread antigovernment behavior. ...
... We provide a theoretical argument demonstrating that governments faced with protest in the context of civil wars are more likely to enter peace agreements and negotiations. Hence, different from the existing literature (e.g., Dudouet 2013;Shellman, Levey, and Young 2013), we attribute violent and nonviolent behavior to different types of actors who subsequently engage in anti-government behavior. ...
... Nilsson (2012) alludes to the role of civil society to attain durable peace after peace settlements, and we further contribute to the nonviolent resistance literature (Chenoweth and Cunningham 2013) by providing a novel theoretical link between violent rebel behavior and anti-government protest. However, different from the existing literature, which theorizes nonviolent and violent behavior as strategic complements, respective substitutes for individual actors and movements (Cunningham, Dahl, and Frugé, forthcoming), or sees violent and nonviolent behavior as part of escalation patterns (Dudouet 2013;Shellman, Levey, and Young 2013), we attribute violent and nonviolent behavior to different types of actors. While violent behavior is used by the core of a rebel organization and initial joiners, nonviolent anti-government behavior can arise from successful rebel organizations' demonstrating government weakness. ...
All rebel organizations start weak, but how do they grow and achieve favorable conflict outcomes? We present a theoretical model that allows for rebel organizations to gain support beyond their “core” and build their bargaining power during fighting. We highlight that rebel organizations need to win over crucial parts of society to generate the necessary support that allows them to attain favorable civil conflict outcomes. We find empirical support for the argument that low‐income individuals who initially fight the government (rebel organizations) have to convince middle‐class individuals to turn out against the government to gain government concessions. Empirically, we demonstrate that government concessions in the form of peace agreements and the onset of negotiations become more likely when protest occurs in the context of civil conflicts.
Replication Materials
The data, code, and any additional materials required to replicate all analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network, at: http://doi.org/10.7910/DVN/MYDZNF .
... In this issue, we see multiple levels of analysis employed to identify causal processes related to nonviolent struggle. The articles included variously study individuals (Davenport & Trivedi, 2013), events (Shellman, Levey & Young, 2013), organizations ( Asal et al., 2013), country-years (Chenoweth & Lewis, 2013;Cunningham, 2013;Rivera Celestino & Gleditsch, 2013), and combinations of micro-level quantitative and qualitative data (Kaplan, 2013). The issue also includes articles whose analysis of comparative cases generates new hypotheses for further inquiry (Nepstad, 2013;Dudouet, 2013). ...
... After a rich overview of civil resistance research (Schock, 2013), the issue proceeds in four substantive parts: explaining the types and use of nonviolent action in different strategic contexts (Part I), the dynamics of contention (Part II), outcomes (Part III), and a special data feature (Part IV). Within these larger themes, the articles focus on a multitude of issues, including the different methods of nonviolent contention available to dissidents (Shellman, Levey & Young, 2013), the determinants of the choice to use nonviolent or violent resistance ( Asal et al., 2013;Chenoweth & Lewis, 2013;Cunningham, 2013;Dudouet, 2013), the determinants and consequences of participation in nonviolent resistance (Davenport & Trivedi, 2013), explaining defection of security forces to nonviolent resistance (Nepstad, 2013), the effects of nonviolent resistance on authoritarian stability (Rivera Celestino & Gleditsch, 2013), and the reasons why armed insurgencies abandon violence in favor of nonviolent resistance (Dudouet, 2013). The articles feature a diverse array of quantitative and qualitative articles, with a number of articles featuring large-N statistical analysis and others featuring comparative cases in the Middle East, North Africa, Latin America, and Asia. ...
... In Part II, Shellman, Levey & Young (2013) demonstrate that the dynamic processes of conflict between state and non-state actors and mass attitudes toward dissident strategies strongly influence when dissident groups choose violence. Nepstad (2013) suggests that security force defections, a potentially key factor for the success of any regime change campaign, are also to some extent dependent on the strategies used by dissidents. ...
The events of the Arab Spring of 2011 have made clear the importance and potential efficacy of nonviolent resistance, as well as the field’s inability to explain the onset and outcome of major nonviolent uprisings. Until recently, conflict scholars have largely ignored nonviolent resistance. This issue features new theoretical and empirical explorations of the causes and consequences of nonviolent resistance, stressing the role that unarmed, organized civilians can play in shaping the course of conflicts. Contributors demonstrate the importance of treating nonviolent and violent strategies, as well as conventional politics strategies, as alternative choices for engaging the state, show how gender ideology can influence which opposition groups use nonviolent resistance, and suggest that the causes of civil war and nonviolent resistance often differ. Other pieces highlight the role of public attitudes regarding whether nonviolent resistance and violence are employed, how experience with activism and repression by the state can shape activists’ perceptions of justice, and how the perceptions of resistance leaders can influence strategic choices. Moreover, several articles examine the key role that security force defections can play in the success of nonviolent resistance, how micro-level nonviolent tactics can improve security in civil war, and how nonviolent campaigns can influence the stability of autocratic states. These contributions suggest that rigorous empirical study of civilian-based contentious politics (rather than only violent contention by armed non-state actors) must be incorporated into the conflict literature. Improved theory and data on the subject will help researchers and policymakers to shape strategies to support these movements when appropriate, and to manage changes in the international system that result from the success of nonviolent uprisings.
... Existing research has treated a social movement's strategy as fixed and disconnected from historical context (see Bruneau et al., 2017;Simpson et al., 2018;Thomas & Louis, 2014). But the ever-changing nature of social realities often demands that a social movement adjust its strategy to achieve its goals (Dudouet, 2013;Duhart, 2017;Shellman et al., 2013). For example, Shellman et al. (2013) suggested there is a state-dissident interaction whereby a nonviolent social movement will shift toward violence because of government repression. ...
... But the ever-changing nature of social realities often demands that a social movement adjust its strategy to achieve its goals (Dudouet, 2013;Duhart, 2017;Shellman et al., 2013). For example, Shellman et al. (2013) suggested there is a state-dissident interaction whereby a nonviolent social movement will shift toward violence because of government repression. Moreover, Grant and Wallace (1991) found that a nonviolent social movement may shift toward violence as a defensive counterstrategy once the sociopolitical context are perceived to be untenable. ...
Across four experimental studies (NStudy 1 = 466, a hypothetical movement in Bhutan, NStudy 2 = 447, a hypothetical movement in the United Kingdom, NStudy 3 = 463, a hypothetical movement in Bhutan, NStudy 4 = 460, a real movement in the United States) and an integrated data analysis, we examined when third parties (i.e., those who are not actively engaged in the movement) will support a social movement that permits the use of violence. In Studies 1–3, third parties were more willing to support violence when it was framed as having shifted to violence when nonviolence failed to achieve their goals. Mediation analyses revealed that a shift toward permitting violence reduced support to the extent that the shift created perceived moral decline in the social movement (Studies 1–3), but increased when the shift was perceived to be a last resort (Study 3). Last, we showed (Study 4) most effects disappear when third parties are told that they may be in close proximity to the violence (Study 4). These suggest third parties can and do support the use of violence as well as when and why such support is offered.
... This hypothesis extends earlier work that finds the same relationship at the movement level, using a movement's reported maximum participation rate. As far as we are aware, existing work on protester violence and outcomes is cross-sectional (Stephan and Chenoweth, 2008;Celestino and Gleditsch, 2013;Chenoweth and Schock, 2015) or focused on its interaction with state tactics (Shellman et al., 2013). It is therefore unclear if protester violence decreases participation, less participation causes protesters to result to violence, or a smaller movements results from another feature. ...
... Measuring repression on a continuous scale may therefore provide a clearer understanding of how it affects protest dynamics. It also facilitates the inclusion and interpretation of interaction terms for violence, allowing us to test for nonlinear effects (Moore, 1998;Shellman et al., 2013). ...
A key determinant of whether social movements achieve their policy goal is how many people protest. How many people protest is in turn partially determined by violence from protesters and state agents. Previous work finds mixed results for violence. This paper reconciles the mixed results for violence by distinguishing between the timing of repression and its severity: low levels of state repression increase protest size while high levels decrease it, conditional on preventative repression failing. It evaluates the role of violence by applying deep learning techniques to geolocated images shared on social media. Across more than 4,300 observations of twenty-four cities from five countries, we find that protester violence is always associated with subsequently smaller protests, while low (high) levels of state violence correlate with increased (decreased) protest size.
... This hypothesis extends earlier work that finds the same relationship at the movement level, using a movement's reported maximum participation rate. As far as we are aware, existing work on protester violence and outcomes is cross-sectional (Stephan and Chenoweth, 2008;Celestino and Gleditsch, 2013;Chenoweth and Schock, 2015) or focused on its interaction with state tactics (Shellman et al., 2013). It is therefore unclear if protester violence decreases participation, less participation causes protesters to result to violence, or a smaller movements results from another feature. ...
... Measuring repression on a continuous scale may therefore provide a clearer understanding of how it affects protest dynamics. It also facilitates the inclusion and interpretation of interaction terms for violence, allowing us to test for nonlinear effects (Moore, 1998;Shellman et al., 2013). ...
A key determinant of whether social movements achieve their policy goal is how many people protest. How many people protest is in turn partially determined by violence from protesters and state agents. Previous work finds mixed results for violence. This paper reconciles the mixed results for violence by distinguishing between the timing of repression and its severity: low levels of state repression increase protest size while high levels decrease it, conditional on preventative repression failing. It evaluates the role of violence by applying deep learning techniques to geolocated images shared on social media. Across more than 4,300 observations of twenty-four cities from five countries, we find that protester violence is always associated with subsequently smaller protests, while low (high) levels of state violence correlate with increased (decreased) protest size.
... Shellman's (e.g. Shellman, 2006a, b;Shellman et al., 2013) work analyzes dynamic interactions of states and dissidents before, during, and after civil war without qualifying periods as war or peace. This latter work is more relevant to what the US government is referring to as the Gray Zone-strategies and tactics between war (black) and peace (white). ...
... Shellman (2006a, b, and2009) focuses on the direction in which actors shift, on a hostility continuum ranging from violence to non-violence, given current relative levels of hostility and cooperation. Shellman et al. (2013) focus on groups' violent vs non-violent phases of behavior. This paper specifically focuses on whether or not groups mix terror and non-terror violent tactics, which we argue is understudied. ...
Many scholars of contentious politics claim there is no such thing as a group that uses only one tactic, yet scholars, pundits, and the public routinely use single-minded terms like protestors, dissidents, and terrorists. Other scholars and research programs suggest that some groups are specialists who tend to stick to a single tactic to achieve their goals, such as non-violence, violence, or specific kinds of violence, like terror. We make the claim that both sides of the debate are empirically valid and that both types of group exist. That is, some groups tend to specialize in a single tactic while others use a variety of tactics. This paper examines the empirical distribution of group types by examining the mix of tactics that groups employ. The analysis helps resolve part of the debate and pushes scholarly thinking in new directions about how often, why, and when groups operate across this spectrum.
... I develop these arguments via a formal model, which provides further novel insights into the dynamics of tactical change in con ict. First, consistent with literature on the repression-dissent nexus (Moore 2000;Shellman, Levey, and Young 2013;Trejo 2012), it shows that groups can change from nonviolent to violent tactics in the face of escalating repression, and violent to nonviolent when governments show increasing restraint in applying repression. In Syria and Libya, nonviolent protesters turned to violence when faced with a commitment to apply severe repression by their governments. ...
... The relationship between repression and tactical change from nonviolence to violence is consistent with the repression-dissent literature, where repression is thought to predictably increase the likelihood that nonviolent dissent turns violent (Moore 2000;Shellman, Levey, and Young 2013). Lichbach (1987), for instance, argues that dissidents seek out the tactic that receives the least amount of repression, and change tactics based on that consideration. ...
... Yet this book also moves us beyond Gamson's study since it is much broader (containing 323 cases versus Gamson's 53 cases) and it does not conflate disruptive with violent tactics, avoiding some of the confusion that arose from Gamson's book. Following Chenoweth and Stephan's landmark work, there has been an incredible surge of publications on nonviolence or civil resistance in mainstream academic disciplines and presses ( Nepstad 2011Nepstad , 2013Nepstad , 2015Nepstad and Kurtz 2012;Nikolayenko 2012;Pearlman 2011;Scalmer 2011;Schock 2015aSchock , 2015bShellman et al. 2013). This explosion of research indicates that the subfield is currently one of the liveliest areas of study within contentious politics realm. ...
... One study found that the shift from nonviolence to violence could be a response to government repression. In their study of Sri Lanka's Tamil Tigers and the Filipino Moro Islamic Liberation Front, Shellman, Levey, and Young (2013) found that movements are more likely to use violent methods when state repression is low and more likely to resort to nonviolent methods when state repression is high. Why? ...
To introduce this special issue, I provide a brief overview of nonviolence or civil resistance research. I explain the origins and development of the field starting with its Gandhian roots, through the pragmatic Sharpian period, to the current state of empirical testing and development of nonviolence theories. I also summarize the field's main findings to date, particularly in the areas of campaign outcomes, long-term consequences of nonviolent revolutionary movements, and tactical shifts from nonviolence to violence and vice versa. Pointing out the civil resistance research questions and findings that complement social movement studies, I call for greater dialogue between these two fields that have largely developed in parallel with few points of crossover. I conclude by overviewing the articles in this special issue, noting how they extend our knowledge, make new contributions, and offer a timely reflection on this burgeoning field-particularly its theoretical blind spots and omissions.
... Recently, however, more scholars have advocated using out-of-sample data to evaluate and compare models (Goldstone et al. 2010;Ward et al. 2012;Hegre et al. 2013;Schrodt et al. 2013). There is now a growing literature developing and applying methods to predict occurrences of rare but destructive events such as civil war (Hegre et al. 2013;Shellman et al. 2013;Brandt et al. 2014;Clayton and Gleditsch 2014), interstate disputes (Gleditsch and Ward 2012), and political instability (Goldstone et al. 2010). If we claim that our theories have implications for events with the potential to affect lives, we should examine whether our theories make correct predictions. ...
... Statistical learning methods like Random Forests have rarely been used in political science (for overviews, see Siroky 2009), but have gained some attention recently (Spirling 2008;Schrodt et al. 2013;Shellman et al. 2013;Hill and Jones 2014;Jones and Linder 2015). Unlike logistic regression, where a statistical model that was likely to have generated that data is specified by the researcher prior to estimation, no "model" in the conventional sense is generated by Random Forests. ...
The most commonly used statistical models of civil war onset fail to correctly predict most occurrences of this rare event
in out-of-sample data. Statistical methods for the analysis of binary data, such as logistic regression, even in their rare
event and regularized forms, perform poorly at prediction. We compare the performance of Random Forests with three versions
of logistic regression (classic logistic regression, Firth rare events logistic regression, and L1-regularized logistic regression), and find that the algorithmic approach provides significantly more accurate predictions
of civil war onset in out-of-sample data than any of the logistic regression models. The article discusses these results and
the ways in which algorithmic statistical methods like Random Forests can be useful to more accurately predict rare events
in conflict data.
... However, it is important to point out that the use of facial emotion recognition in this regard has been mainly theorized and real-world applications have been sparse. On the other hand, text-based sentiment analysis has proven promising in predicting political shifts in dissidents organizations [53]. As for the case of crime prevention, we can currently only infer possible interactions between emotion recognition and social metaverses. ...
In this paper, we look at the latest developments in the field of online virtual realities, with particular focus on “metaverses”. Within this field, we aim to describe potential interactions with emotion recognition and manipulation technologies. The article points out how these technologies can generate new threats to human and individual rights. Moreover, it covers how already existing uses of these technologies can become increasingly worrying in the context of metaverses. Finally, we look at existing legal and technical protections; we focus on their success and their shortcomings and how they can be improved in order to adapt to these new technologies. Our research question was: how can emotion recognition and manipulation technology be used and/or abused in the context of a metaverse?
... Besides the onset or incidence of civil war, conflict scholars predict a wide variety of violent outcomes, such as genocide (Harff 2003;Pilster et al. 2016), state-led mass killing (Koren 2017), state repression (Gohdes and Carey 2017), phase shifts between violent and nonviolent resistance (Shellman et al. 2013), political violence more generally (Weidmann and Ward 2010;Bell et al. 2013), irregular leadership changes (Beger et al. 2014;Ward and Beger 2017), state failure (King and Zeng 2001), political instability (O'Brien 2002;, ethnic conflict (Bara 2014;, inter-state conflict (Beck et al. 2000;, or maritime piracy Prins 2015, 2017a), to list just a few. Increasingly, scholars also aim to go beyond binary outcomes and instead predict the level or intensity of violence (e.g. ...
... 32 Although existing work has made significant progress toward understanding why non-state actors target civilians, less is known about what drives escalations in this violence. 33 Some theories of violence against civilians (committed by any actor) postulate overall trends. For example, Kalyvas 34 anticipates that violence will start slowly, increase rapidly, and decrease again in response to changes in relative territorial control, but does not make more specific predictions about the precise timing of changes in violence. ...
Although past research has addressed why civilians are targeted, we know less about why non-state actors escalate violence against civilians at particular times. This article seeks to identify the events that trigger spikes in violence against civilians committed by non-state actors. We employ an innovative method to identify 24 such escalations in Africa committed by 20 different non-state groups between 1989 and 2015. Rigorous case studies reveal three major types of triggers, including situations in which (1) groups lose relative power, (2) groups gain relative power, and (3) opponents attack civilians. Specifically, we find that opponent military advances—which results in a relative loss of power for the non-state actor—are the most common trigger. More broadly, 75 percent of all escalations are tied to a group’s relative loss in power. These results improve understandings of civilian targeting by non-state actors and may inform efforts to forecast such violence before it occurs.
... With regard to spatial variation, some studies have found local constituency bases (Ottmann 2017;Fjelde and Hultman 2014), preexisting networks and support (Holtermann 2016;Balcells 2011), the level of local control (Kalyvas 2006), or the presence of competition with other armed groups (Metelits 2009) to be significant determinants for the use of violence against civilians. In terms of temporal variation, some authors have foregrounded explanations connected to the war dynamics themselves, specifically with regard to shifting balances of power (Holtermann 2016) or the degree of state repression (Shellman, Levey, and Young 2013;Asal et al. 2019). Horowitz, Perkoski, and Potter (2018) demonstrate that violent state response and intergroup competition enhance the tendency for tactical diversification among armed groups. ...
Research on rebel behavior during conflicts has traditionally focused on the use of violent tactics. However, evidence from several intrastate wars suggests that armed groups also occasionally employ general strikes—a method of civil resistance that has typically been associated with nonviolent groups. But when do rebels resort to general strikes? I argue that these tactics have a particular function which can offset potential risks for rebels after they have suffered losses in previous battles: Through general strikes, rebels signal sustained authority to the local population. The argument is tested for districts in Eastern India using newly compiled, disaggregated data on contentious action during the Maoist conflict. The paper contributes to a burgeoning literature on wartime civilian activism in two ways: First, it shows that armed groups themselves rely situationally on civilian mobilization. Second, it investigates the effect of conditions endogenous to the conflict on these tactical choices.
... This was a good start for the relationship between the Central Government of the Philippines and the Muslim separatist movement in Southern Mindanao. But the results of the Tripoli Agreement did not produce a long-lasting peace, because there were differences on the implementation process of the agreement, the partial control of Ferdinand Marcos without considering the interest of the rebelling party, and the internal dispute over ideologies and strategic shifts inside the MNLF, which resulted in the formation of a breakaway fraction-MILF, led by Hashim Salamat(Bertrand, 2014;Levey, Shellman, & Young, 2013).The Jeddah Accord 1987 was the second attempt by President Corazon Aquino to open a re-negotiation between the Filipino government and MNLF in Jeddah, Saudi Arabia, after a meeting with Nur Miswari, MNLF leader, seeking for mediation assistance from OIC. Accordingly, MNLF agreed to make peace by accepting the concept of autonomy for Muslim Mindanao as a new clause that would be raised in the Philippines' Constitution(Abubakar, 2019). However, this agreement failed and reached a deadlock at the Filipino Congress, pushing MNLF leaders to call on President Corazon Aquino to issue an executive decision to grant autonomy to Muslim Mindanao. ...
This article investigates the quality of peace in armed conflicts that occurred in the Southeast Asia region. The authors compared the cases of Aceh, where the armed conflict between the Free Aceh Movement or GAM and the government of Republic Indonesia ended peacefully with the Helsinki Memorandum of Understanding, with the conflict in the southern Philippines, where a peace agreement, the Comprehensive Agreement on the Bangsamoro, was successfully achieved between the government of Philippines and the Moro Islamic Liberation Front. This research employed document analysis to analyse the peace settlement documents of both parties and the derivative laws of the agreed settlements, as well as other relevant sources as the secondary data. All documents and sources were processed through the NVivo 12 application. The findings revealed that in both Aceh and Bangsamoro, the quality of peace is far from significant, for not all the terms of the agreements had been realised and there was still mutual suspicion prevailing between the two fighting parties. Therefore, what had been agreed upon in the Aceh and Bangsamoro post-conflict agreements must be accomplished as they should be in order to create a lasting peace, thereby allowing the people to experience a sufficient quality peace together.
... Besides the onset or incidence of civil war, conflict scholars predict a wide variety of violent outcomes, such as genocide (Harff 2003;Goldsmith et al. 2013;Pilster et al. 2016), state-led mass killing (Koren 2017), state repression (Gohdes and Carey 2017), phase shifts between violent and nonviolent resistance (Shellman et al. 2013), political violence more generally (Weidmann and Ward 2010;Bell et al. 2013), irregular leadership changes (Beger et al. 2014;Ward and Beger 2017), state failure (King and Zeng 2001), political instability (O'Brien 2002;Goldstone et al. 2010;O'Brien 2010), ethnic conflict (Bara 2014;, inter-state conflict (Beck et al. 2000;Gleditsch and Ward 2013), or maritime piracy Prins 2015, 2017a), to list just a few. Increasingly, scholars also aim to go beyond binary outcomes and instead predict the level or intensity of violence (e.g. ...
... "Selection bias" here refers to the fact that newspapers choose which events merit coverage, leading to distorted inferences about those events and the larger universe of events (Baum and Zhukov 2015;Donnay 2017;Myers and Caniglia 2004;Weidmann 2015). "Fatigue bias" refers to newspapers' predilection to favor novel events and human coders' quick loss of acuity during repetitive coding (Gerner and Schrodt 1998;Masad 2013;Shellman, Levey, and Young 2013). Because social media is not space constrained and computers do not fatigue, images for event data should suffer less bias than do current text approaches. 2 Zhang and Pan mention three other weaknesses of social media; again, I applaud them for their modesty but am less reserved. ...
... Terrorism may also represent a special case of the repression-protest paradox. Violence and radicalization is one possible outcome of repression as moderates leave a movement and opportunities for nonviolent engagement are decreased (Beck 2015;Della Porta 1995;Piazza 2006;Shellman, Levey, and Young 2013). This is a common finding among terrorism researchers, even as they fail to make the theoretical connection. ...
In spite of a proliferation of empirical research, scholarship on terrorism remains theoretically fragmented and often inconclusive on even basic issues. This chapter details how terrorism can be incorporated into the social movements and collective action scholarships’ portfolio of research through a review of several of the most widely debated topics in current terrorism research: (1) how terrorism is defined; (2) dynamics of radicalization for individuals and groups; (3) intensity and targets of violence; (4) organizational diversification; and (5) the context of terrorist action. Taking a problem‐centered approach, it details how prior insights from scholarship on social movements and collective action can theoretically and substantively advance terrorism research.
... First, and perhaps most importantly, the repression-dissent research program largely embraces a set of assumptions about structure and strategic interaction that proponents of the civil resistance literature largely reject. Specifically, many repression-dissent scholars suggest that nonviolent and violent resistance techniques are largely substitutable for one another and that increases in repression tend to predictably increase the probability that nonviolent dissent becomes violent (Shellman, Levey, and Young 2013;Moore 1995Moore , 1998Moore , 2000Lichbach 1998;Lehoucq 2016). Otherwise, some argue that certain thresholds of repression entirely preclude the use of nonviolent dissent, leading dissidents instead to choose violence at the outset of a campaign (Trejo 2012;Lehoucq 2016;Pearlman 2012). ...
In this article, we review decades of research on state repression and nonviolent resistance. We argue that these two research programs have converged around six consensus findings. We also highlight several areas of divergence, where greater synthesis between the research on state repression and nonviolent resistance might prove useful. We draw attention to remaining controversies surrounding the association between state repression and nonviolent resistance—particularly regarding different theoretical assumptions about structure, agency, and strategic choice; measurement challenges for both repression and dissent; methodological challenges regarding endogeneity, multicausality, and equifinality; and moral hazards associated with the study of nonviolent resistance and the effectiveness of repression. We conclude by highlighting some productive ways forward.
... The "aha" moment in research focusing upon the need to rethink how to forecast violence or anticipate threats occurred following the discovery that the inclusion of sentiment variables, along with events analysis variables, markedly improved the ability to forecast the advent and cessation of violence (Shellman, et. al., 2013a). This began a sequence of US Air Force Research Laboratory efforts focused on identification and interpretation of discourse and discursive behaviors that enable anticipatory analysis (early indicators or "signals"), which precede a future event or behavior (e.g., violent event). The research is focused on developing both methods and te ...
Herein, MAJ Gregory Seese, MAJ Shawn Stangle, CPT Robby
Otwell, SFC Matthew Martin, and LTC Rafael Linera provide a broad overview of significant
improvements in the understanding of human cognitive processes afforded by recent
developments in neuroscience. These methods show that traditional collection approaches fail
to provide holistically effective metrics to plan and assess modern persuasive efforts. The
authors note that media neuroscience techniques that where once cost prohibitive and
confined to a laboratory are now affordable, compact, and mobile. They argue that USASOC
can capitalize on recent advancements in media neuroscience and integrate the field’s most
currently available equipment, training, and techniques into the PSYOP force. This new
technology can be leveraged to augment and enhance the existing social/behavioral science
methods presently in use. This will then contribute to an increase in the effectiveness of DoD
influence campaigns, as it modernizes both the practices and equipment used within the PSYOP
Force.
Conventional and tired characterizations of civil wars invoke images of endless chaos and relentless violence perpetuated by armed groups. In reality, civil wars are defned by unique forms of wartime social and political order, and are anything but chaotic.1 This study focuses on ‘rebel governance’ as a specifc rebel-civilian sociopolitical relationship in which rebel groups participate in the administration of civilian afairs. Using disaggregated data on rebel governance in 122 civil wars, I examine the relationship between the character of rebel governance used by rebel groups and the use of violence against civilians. Contrary to existing characterizations of rebel governance, the results of the large-N analysis show rebel governance, particularly the provision of social services, to be positively related to confict violence. Through further qualitative analysis of governance in the case of the Liberation Tigers of Tamil Eelam (LTTE), I point to the necessary role of violence in the administration of rebel governance and rebel group capacity as two preliminary explanations for the observed relationship.
One of the unresolved puzzles in the civil resistance and contentious politics literatures is why some movements that begin seeking limited redress in a certain policy space escalate their claims to demand the ousting of a national leader or the entire regime, a process the article terms ‘demand escalation’. For instance, in the summer of 2019, thousands took to the streets of Hong Kong to protest about a proposed extradition bill that would allow criminal suspects to be sent to mainland China to face trial in courts controlled by the Communist Party. However, even after Hong Kong’s leader, Carrie Lam, announced the formal withdrawal of the controversial bill, protests continued with some calling for greater democracy and others demanding Lam’s resignation. Whereas most of the literature on civil resistance treats demands as fixed and focuses on different methods of struggle to pursue predefined ends, this article shows that demands can change as a result of the state–dissent interaction. The article argues that movements are more likely to escalate their demands when the state responds to the initial nonviolent action with a disproportionate use of force, because such an action intensifies the grievances the protesters have against the state and betrays the remaining trust that people might have had in the government. The analysis of a new quantitative dataset that catalogues both reformist and maximalist opposition campaigns globally supports this claim. By incorporating non-maximalist campaigns into the analysis and not treating demands as fixed, this article adds to our understanding of mass campaigns and highlights an overlooked means by which nonviolent campaigns can up their ante without resorting to violence.
Spatial interdependencies commonly drive the spread of violence in civil conflict. To address such interdependence, scholars often use spatial lags to model the diffusion of violence, but this requires an explicit operationalization of the connectivity matrices that represent the spread of conflict. Unfortunately, in many cases, there are multiple competing processes that facilitate the spread of violence making it difficult to identify the true data-generating process. We show how a network-driven methodology can allow us to account for the spread of violence, even in the cases where we cannot directly measure the factors that drive diffusion. To do so, we estimate a latent connectivity matrix that captures a variety of possible diffusion patterns. We use this procedure to study intrastate conflict in eight conflict-prone countries and show how our framework enables substantially better predictive performance than canonical spatial-lag measures. We also investigate the circumstances under which canonical spatial lags suffice and those under which a latent network approach is beneficial.
In this study, we examine the individual-level characteristics of extremists’ pursuit of chemical/biological (CB) agents. Using three different maximum likelihood estimation techniques, we identify three key findings. First, older extremists are more likely to pursue CB than younger extremists. Second, extremists who are jobless or students are more likely to pursue CB than employed extremists. Third, Islamist, far-right, and far-left extremists are less likely to pursue CB than single-issue extremists. We do not find any evidence that gender or education have an effect on whether an extremist will pursue CB agents. Since there has been little quantitative examination of unconventional weapon choices among violent extremists, this study makes an important contribution to the literature on CB adversaries.
This chapter focuses on the theoretical and conceptual underpinnings of conflict with the aim of situating the Niger Delta conflicts within the wider conflict literature. It sets out the conceptual understandings of the dynamics of nonviolence and violence in conflicts that include social movements, contention, structure and agency and the construction of collective narratives. The chapter is structured to show the importance of understanding the dynamics of choice between violence and nonviolence when attempting to analyse the Niger Delta conflicts. This is because research into this topic requires the survey of such diverse literature that makes it necessary to examine theoretical concepts such as contention, construction of collective narratives and identities, social movements, structure and agency. This chapter sets out a theoretical and analytical framework that uses the theories to elucidate the concepts used in the book.
The long-running Muslim insurgency that emerged in the 1970s in the Southern Philippines has preoccupied successive Philippine governments. Previous attempts at negotiations between the leaders of the minority Muslim community and the Philippine government have not succeeded in bringing about durable peace. While the government achieved important milestones in peace negotiations with one Muslim group, the Moro National Liberation Front (MNLF), with the creation of an autonomous Muslim region in 1990 and the signing of a peace agreement in 1996, long-term grievances over territory, economic and political marginalisation continued to persist. This chapter addresses the various attempts made by the government to engage the other large Muslim group, the Moro Islamic Liberation Front (MILF), and focuses on peace negotiations between 1997 and 2014 culminating in the signing of a major peace agreement, the Comprehensive Agreement on the Bangsamoro. It explores the dynamics of peace negotiations through several stages in the conflict and the calculations of actors in crafting formulas for continued engagement. The inherent nature of the conflict puts enormous pressure on the various actors, undermining their ability to seize opportunities, improve their bargaining position and resolve their differences.
This study argues that escalation and de-escalation processes lie at the heart of protest campaigns. These processes are largely determined by the interactions between protesters and governments, as well as the timing and types of strategies and tactics employed. The study examines the dynamics between the Turkish government and the protesters during the 2013 Gezi Protest Campaign. This campaign escalated quickly by generating massive support from different segments of Turkish society in its earlier days, and then de-escalated and eventually demobilized without securing major concessions. By using original data collected from a Turkish newspaper, Cumhuriyet, the study illustrates how the trajectory of the Gezi campaign changed in response to the interactive dynamics between the government and the dissidents.
Automated event data extraction techniques have revolutionized the study of conflict dynamics through the ability of these techniques to generate large volumes of timely data measuring dynamic interactions among actors around the world. In this paper, we describe our approach for adapting these techniques to extract data on sentiments and emotions, which are theorized to crucially contribute to escalating and de-escalating conflict. Political scientists view political conflict as resulting from a series of strategic interactions between groups and individuals. Psychologists highlight additional factors in political conflict, such as endorsements and condemnations, the public's attitude toward its leaders, the impact of public attitudes on policy, and decisions to engage in armed conflict. This project combines these two approaches to examine hypotheses regarding the effects that different emotional impulses have on government and dissident decisions to escalate or de-escalate their use of hostility and violence. Across the two cases examined-the democratic Philippines and authoritative Egypt between 2001 and 2012-we found consistent evidence that intense societal fear of dissidents and societal disgust toward the government were associated with increases in dissident hostility. Conversely, societal anger toward dissidents was associated with a reduction in dissident hostility. However, we also found noticeable differences between the two regimes. We close the article with a summary of these similarities and differences, along with an assessment of their implications for future conflict studies.
Researchers generally examine how variables directly affect events in war. Some variables, however, may not simply increase or decrease conflict events but may instead displace them. In wartime, this dynamic may result from the conditional decision-making made by militaries constrained, at least partially, by time. When there is a necessary regularity to military operations, decision-making may be complicated by factors such as inclement weather, and this regularized pressure to act may produce a hydraulic relationship between inclement weather and events. In this dynamic, today’s inclement weather, such as rain, may displace today’s events. Conversely, yesterday’s rain may increase today’s, with planned events postponed. Similarly, tomorrow’s rain may also increase today’s events, with planned activities moved forward. We test this hydraulic argument with geo-referenced data from the recent Ugandan civil war and find significant evidence that conflict events are fluid in time. Inclement weather constrains and also displaces events.
Is predicting the international community’s cumulative response to an interstate dispute possible? Can we predict what form conflict management will take and how it will evolve over the course of a dispute? I employ the concept of a conflict management trajectory to test a forecasting model of conflict management. This model accurately predicts conflict management behavior and uncovers numerous novel insights—including that the initial intervention indicates clearly the resources the international community is willing to spend on managing the dispute. These results confirm the need to theorize further about conflict management interdependence and offer clear advice to the policy community.
Whereas optimists see the so-called Arab Spring as similar to the revolutions of 1989, and likely to bring about democratic rule, skeptics fear that protest bringing down dictators may simply give way to new dictatorships, as in the Iranian revolution. Existing research on transitions has largely neglected the role of protest and direct action in destabilizing autocracies and promoting democracy. We argue that protest and direct action can promote transitions in autocracies, and that the mode of direct action, that is, whether violent or nonviolent, has a major impact on the prospects for autocratic survival and democracy. We present empirical results supporting our claim that nonviolent protests substantially increase the likelihood of transitions to democracy, especially under favorable international environments, while violent direct action is less effective in undermining autocracies overall, and makes transitions to new autocracies relatively more likely.
This article provides an overview of the practice and study of civil resistance. First, historical roots of modern civil resistance are discussed, including the emergence in the 19th century of mass-based campaigns of non-cooperation to promote nationalist and labor interests, as well as the significance of Mohandas Gandhi and the widespread use of nonviolent resistance in the 20th century. Second, perspectives of scholars of social movements and revolution are compared with those of scholars who focus more specifically on nonviolent resistance. Despite studying much of the same phenomena, separate literatures have developed that are ripe for cross-fertilization and synthesis. In the third section, a literature review is organized around three key concepts for understanding civil resistance: mobilization, resilience, and leverage. Fourth, consequences of nonviolent resistance relative to violent resistance are discussed. Finally, areas for future research are identified.
A theoretical model is proposed explaining why repression sometimes deters and sometimes instigates political action. Then this model is applied to explain the mounting protests in East Germany in 1989. The basic idea of the model is that repression, as a cost, has a direct deterring effect on political action, but that increasing repression instigates positive incentives up to a certain point; then positive incentives decrease-a relationship corresponding to an inverted u-curve. Apart from repression, public goods incentives (discontent, weighted by perceived political influence), moral incentives, and social incentives have positive effects on participation in protest. A representative survey of 1,300 citizens from Leipzig (East Germany) conducted in the fall of 1990, focusing on the events of the East German revolution in 1989, confirms the model with two exceptions: Increasing probability of repression raises protest, but the increase becomes smaller with increasing probability of repression (decreasing radicalization effect); increasing costs of repression lowers protest, but the decrease becomes smaller with increasing costs of repression (decreasing deterrence effect). It is argued that the protests in East Germany could emerge despite severe repression because positive incentives to protest increased due to political events.
Competing hypotheses on the relationship between government and dissident behavior emerge from both formal and empirical models. Yet, the current literature lacks a comprehensive theoretical account of such contradictory effects. This study develops a theory to account for a large number of competing hypotheses within a single framework. The theory explains various government and dissident tactical choices over the course of an internal political struggle by focusing on leaders, their motivations, and the link between their motivations and actions. The theory gives rise to a process model of sequential government-dissident interactions that is used to test several implied hypotheses. Empirical sequential time-series models of government and dissident behavior find support for most of the theory's implied hypotheses in Israel (1979–2002) and Afghanistan (1990–99).
King, Keohane, and Verba (1994, pp. 27-28) argue that we should "maximize the validity of our measurement," "ensure that data-collection methods are reliable," and make all data and analysis replicable. In an effort to improve the measurement of the events data collected by the Intranational Political Interactions (IPI) project, this extension of the project produces two new valid and reliable interval-like scales. Following Azar (1982), Goldstein (1992), and Moore and Lindstrom (1996), I produce interval-like scales of cooperative and hostile political actions based on a group of experts' judgements. The collective scaling procedure produces data suitable for use in OLS regression models as well as a standardized interval-like scale that more accurately represents the true scores of event types. The paper discusses the procedures taken to derive the new measures, proceeds to argue why the new measures are improvements over existing measures, and reports the findings of statistical analytic comparisons. The statistical comparisons demonstrate that the new scales make a difference in various statistical models using different temporal units of aggregation.
The historical record indicates that nonviolent campaigns have been more successful than armed campaigns in achieving ultimate goals in political struggles, even when used against similar opponents and in the face of repression. Nonviolent campaigns are more likely to win legitimacy, attract widespread domestic and international support, neutralize the opponent's security forces, and compel loyalty shifts among erstwhile opponent supporters than are armed campaigns, which enjoin the active support of a relatively small number of people, offer the opponent a justification for violent counterattacks, and are less likely to prompt loyalty shifts and defections. An original, aggregate data set of all known major nonviolent and violent resistance campaigns from 1900 to 2006 is used to test these claims. These dynamics are further explored in case studies of resistance campaigns in Southeast Asia that have featured periods of both violent and nonviolent resistance.
To investigate the implications of source selection, three different sources regarding Guatemalan state terror are compared: newspapers, human rights documents, and interviews with eyewitnesses. Results show that each source pays attention to diverse types and aspects of repression in line with the objectives of the observer, the characteristics of the repressive events, and the overall political context within which events take place. Who is consulted influences what is observed/recorded. Suggestions are presented for understanding sociopolitical behavior through diverse data sources, especially behavior related to contentious activity and/or occurring within contexts that are not easily penetrable.
Previous quantitative research on ethnic civil war relies on macro-level proxies in an attempt to specify the conditions under which ethnic minorities rebel. Going beyond an exclusive focus on minorities, the present study employs Geographic Information Systems (GIS) as a way to model ethnic center—periphery dyads that confront governments with excluded groups. We construct and analyze a new dataset of geo-referenced politically relevant ethnic groups, covering the entire world during the period from 1951 through 2005. Our results show that the conflict probability of marginalized groups increases with the demographic power balance compared to the group(s) in power. Furthermore, the risk of conflict increases with the distance from the group to the capital, and the roughness of the terrain in the group's settlement area. We also find that while the results for demographic group strength hold for all ethnic civil wars, the geographic factors apply for territorial ethnic conflicts only.
Theories of conflict emphasize dyadic interaction, yet existing empirical studies of civil war focus largely on state attributes and pay little attention to nonstate antagonists. We recast civil war in a dyadic perspective, and consider how nonstate actor attributes and their relationship to the state influence conflict dynamics. We argue that strong rebels, who pose a military challenge to the government, are likely to lead to short wars and concessions. Conflicts where rebels seem weak can become prolonged if rebels can operate in the periphery so as to defy a government victory yet are not strong enough to extract concessions. Conflicts should be shorter when potential insurgents can rely on alternative political means to violence. We examine these hypotheses in a dyadic analysis of civil war duration and outcomes, using new data on nonstate actors and conflict attributes, finding support for many of our conjectures.
Why are some terrorist organizations so much more deadly then others? This article examines organizational characteristics such as ideology, size, age, state sponsorship, alliance connections, and control of territory while controlling for factors that may also influence lethality, including the political system and relative wealth of the country in which the organization is based. Using data from the Memorial Institute for the Prevention of Terrorism's Terrorism Knowledge Base (TKB), we use a negative binomial model of organizational lethality, finding that organizational size, ideology, territorial control, and connectedness are important predictors of lethality while state sponsorship, organizational age, and host country characteristics are not.
Recent analyses of civil war have suggested that these events grow out of lower-level conflict dynamics involving state repression and political dissent. Unfortunately, existing work has either indirectly measured escalation or considered only one argument in isolation of others. Examining 149 countries from 1976 to 1999, we develop new measurements for lower-level conflict and explore alternative explanations for conflict escalation. Our results disclose that there is no single theory of escalation to civil war but rather there are several,
which explain different civil wars. This research has significant implications for how we understand and examine the origins of large-scale conflict.
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This article describes a new machine-coded event data set specifically designed to study the spatially, temporally, and tactically disaggregated actions of multiple state and nonstate actors in a systematic fashion. The project develops an extensive set of dictionaries for multiple actors and employs a new coding scheme to organize information on such actors and their behavior. The author describes the machine content-analysis methods used to collect the data and the newly developed coding scheme.
This paper describes in technical detail the Kansas Event Data System (KEDS) and summarizes our experience in coding Reuters data for the Middle East. The components of KEDS are first described; this discussion is intended to provide sufficient detail about the program that one could develop a more sophisticated machine-coding system based on our research. We then discuss a number of problems we have encountered in machine coding, focusing on the Reuters data source and the KEDS program itself. The paper concludes with a discussion of future approaches to machine coding in event data research and other potential applications of the technology. Keywords. event data, natural language, full-text databases, international relations, social science.
State repression includes harassment, surveillance/spying, bans, arrests, torture, and mass killing by government agents and/or affiliates within their territorial jurisdiction. Over the past 40 years, the systematic study of state repression has grown considerably. The development of this work, however, has been uneven. Though unified in their focus on the problem of order (i.e., trying to ascertain how political authorities wield coercive power amid potential and actual domestic challengers), different scholars tend to emphasize distinct aspects of the topic. Consequently, a great deal of progress has been made in specific areas but others have lagged behind. In this review, I attempt to identify the dominant traditions in the repression literature, the core empirical findings, and some persisting puzzles.
Large-n studies of conflict have produced a large number of statistically significant results but little accurate guidance in terms of anticipating the onset of conflict. The authors argue that too much attention has been paid to finding statistically significant relationships, while too little attention has been paid to finding variables that improve our ability to predict civil wars. The result can be a distorted view of what matters most to the onset of conflict. Although these models may not be intended to be predictive models, prescriptions based on these models are generally based on statistical significance, and the predictive attributes of the underlying models are generally ignored. These predictions should not be ignored, but rather need to be heuristically evaluated because they may shed light on the veracity of the models. In this study, the authors conduct a side-by-side comparison of the statistical significance and predictive power of the different variables used in two of the most influential models of civil war. The results provide a clear demonstration of how potentially misleading the traditional focus on statistical significance can be. Until out-of-sample heuristics - especially including predictions - are part of the normal evaluative tools in conflict research, we are unlikely to make sufficient theoretical progress beyond broad statements that point to GDP per capita and population as the major causal factors accounting for civil war onset.
In the last twenty years, an international group of political scientists has coded nearly 2000 party manifestos with the help of one single coding scheme based on 56 categories which covers all main topics of these documents. However, there is a growing awareness of the shortcomings of the underlying coding scheme, such as overlapping and missing categories, which cannot be repaired without coding all manifestos all over again. Some have presented an alternative for manifesto-research by means of expert opinions on party policy positions, but these are unable to provide reliable time series for subsequent election years. The unborn solution to some of the problems with the coding scheme would be the computerised content analysis on digitalised party manifestos. This would open up a new universe of infinite possibilities for recodings and reanalyses. The extended consequences from full computerisation of textual analysis are mind boggling. But at the present, these possibilities are merely potentials as the computerised techniques are still underdeveloped. This article explores the possibilities for computerised content analysis in such a way that all postwar manifestos in established democracies can be compared with each other with the help of flexible coding schemes.
While many areas of research in political science draw inferences from temporally aggregated data, rarely have researchers explored how temporal aggregation biases parameter estimates. With some notable exceptions (Freeman 1989, Political Analysis 1:61–98; Alt et al. 2001, Political Analysis 9:21–44; Thomas 2002, “Event Data Analysis and Threats from Temporal Aggregation”) political science studies largely ignore how temporal aggregation affects our inferences. This article expands upon others' work on this issue by assessing the effect of temporal aggregation decisions on vector autoregressive (VAR) parameter estimates, significance levels, Granger causality tests, and impulse response functions. While the study is relevant to all fields in political science, the results directly apply to event data studies of conflict and cooperation. The findings imply that political scientists should be wary of the impact that temporal aggregation has on statistical inference.
An influential conventional wisdom holds that civil wars proliferated rapidly with the end of the Cold War and that the root cause of many or most of these has been ethnic nationalism. We show that the current prevalence of internal war is mainly the result of a steady accumulation of protracted conflicts since the 50s and 60s rather than a sudden change associated with a new, post-Cold War international system. We also find that after controlling for per capita income, more ethnically or religiously diverse countries have been no more likely to experience significant civil violence in this period. We argue for understanding civil war in this period in terms of insurgency or rural guerrilla warfare, a particular form of military practice that can be harnessed to diverse political agendas, including but not limited to ethnic nationalism. The factors that explain which countries have been at risk for civil war are not their ethnic or religious characteristics but rather the conditions that favor insurgency. These include poverty, which marks financially and bureaucratically weak states and also favors rebel recruitment, political instability, rough terrain, and large populations.
: This paper discusses the experience of the Kansas Event Data System (KEDS) project in developing event data sets for monitoring conflict levels in five geographical areas: the Levant (Arab-Israeli conflict), Persian Gulf, former Yugoslavia, Central Asia (Afghanistan, Armenia-Azerbijan, former Soviet republics), and West Africa (Liberia, Sierra Leone). These data sets were coded from commercial news sources using the KEDS and TABARI automated coding systems. The paper discusses our experience in developing the dictionaries required for this coding, the problems with the number of reported events in the various areas, and provides examples of the statistical summaries that can be produced from event data. We also compare the coverage of the Reuters and Agence France Presse news services for selected years in the Levant and former Yugoslavia. We conclude with suggestions for four topics where additional efforts that could be usefully undertaken by multiple research projects. The coding software, coding dictionaries and data are available at the KEDS web site, http://www.ku.edu/~keds. Schrodt, Simpson and Gerner Page 1 1.
No Other Way Out provides a powerful explanation for the emergence of popular revolutionary movements, and the occurrence of actual revolutions, during the Cold War era. This sweeping study ranges from Southeast Asia in the 1940s and 1950s to Central America in the 1970s and 1980s and Eastern Europe in 1989. Following in the 'state-centered' tradition of Theda Skocpol's States and Social Revolutions and Jack Goldstone's Revolutions and Rebellion in the Early Modern World, Goodwin demonstrates how the actions of specific types of authoritarian regimes unwittingly channeled popular resistance into radical and often violent directions. Revolution became the 'only way out', to use Trotsky's formulation, for the opponents of these intransigent regimes. By comparing the historical trajectories of more than a dozen countries, Goodwin also shows how revolutionaries were sometimes able to create, and not simply exploit, opportunities for seizing state power.
In this article, the authors develop and empirically evaluate a general model of the linkages between domestic and international conflict behavior. Much of the literature on domestic international interactions has focused on the structural constraints of the international and domestic systems on leaders' foreign policy decisions. Rather than focusing on structural constraints, the present authors model the influence of the behavior of domestic and international rivals on leader decision making. The impact of rivals' behavior on conflict across the domestic-international nexus has been neglected relative to the role of structural factors. This study helps redress that imbalance. The authors test their model with a statistical analysis of Zaire during the period 1975 to 1992 and find substantial support for the model.
We investigate the causes of civil war, using a new data set of wars during 1960-99. Rebellion may be explained by atypically severe grievances, such as high inequality, a lack of political rights, or ethnic and religious divisions in society. Alternatively, it might be explained by atypical opportunities for building a rebel organization. While it is difficult to find proxies for grievances and opportunities, we find that political and social variables that are most obviously related to grievances have little explanatory power. By contrast, economic variables, which could proxy some grievances but are perhaps more obviously related to the viability of rebellion, provide considerably more explanatory power.
I investigate how and why the Shah's policies of accommodation and repression escalated the revolutionary mobilization of the Iranian population. Several major theories--micromobilization theory, value expectancy, and bandwagon (critical mass) models--are used to sort out the empirical relationships between protest behavior (violent and nonviolent), strikes, spatial diffusion, concessions, and repression in the year prior to the Shah's exit from Iran. Estimates from Poisson regression models show that repression had a short-term negative effect and a long-term positive effect on overall levels of protest via repression's influence on spatial diffusion. I infer that this pattern of effects stems from a combination of deterrent and micromobilization mechanisms. Concessions expanded the protests by accelerating massive urban strikes that in turn generated more opposition activity throughout Iran. Spatial diffusion was encouraged by government concessions and massive labor strikes. Mutually reinforcing relationships between concessions, strikes, and spatial diffusion indicate the significance of intergroup dynamics in the revolutionary process.
Theory: Two expected utility theories and one psychological/resource mobilization theory of the impact of repression on dissent are tested in this study. Hypotheses: Lichbach (1987) hypothesizes that dissidents will substitute violent protest for nonviolent protest behavior (and vice versa) when confronted with repression. Gupta, Singh, and Sprague (1993) put forth a contextual argument: repression spurs violence in democracies, but high levels of repression are effective in authoritarian regimes. Rasler (1996) contends that timing matters: repression is effective in the short run, but spurs pro-test in the long run. Methods: Sequential tests of events data are used to test the hypotheses. Results: Lichbach's theory is supported by the evidence, but neither Gupta, Singh, and Sprague's nor Rasler's theories receives support.
The relationship between coercion and protest, arguably the core of any theory of rebellion, remains unresolved. Competing hypotheses have emerged from formal models and empirical research. This article uses two forms of the predator-prey model to test these competing hypotheses. Time-series data from three coercive states (the German Democratic Republic, Czechoslovakia, and the Palestinian Intifada) are used to estimate parameters for both models. Results show stable, damped relationships in all three cases. The “inverted U” hypothesis receives less support than its “backlash” alternative, that is, that dissidents react strongly to extremely harsh coercion. Moreover, the study indicates that protesters adapt to coercion by changing tactics.
Scholars argue that third parties make rational calculations and intervene to influence interstate dispute outcomes in favor of their own objectives. Third parties affect not only conflict outcomes but also escalation and duration. Theories of third-party involvement are applied to understand the dynamics of intrastate war. An analysis of event data for three Central American conflicts (El Salvador, Guatemala, and Nicaragua) from 1984 to 2001 is used to examine transnational actors’ influence on the dynamics of civil war. Findings show that transnational third parties often alter levels of cooperation among domestic adversaries, and that consistency affects the strength and direction of third-party influence.
This article describes a substitution model of states' responses to dissident behavior and a statistical test of some sequential hypotheses that are derived from the model. It is motivated by an interest in understanding the sequential response of states to dissident activity. That is, if dissidents protest, what will the state do next? Similarly, if dissidents are cooperative, what will the state do next? The author argues that the answer to both of these questions depends on the interaction of the state's most recent behavior (i.e., repression or accommodation) and the dissident's response. The model produces the hypothesis that states substitute repression for accommodation, and vice versa, in response to dissident protest. Statistical analysis of evidence from Peru and Sri Lanka, 1955 to 1991, suggests that the model captures well the sequential responses of the Peruvian and Sri Lankan governments to dissident behavior during that period.
In this article, the author makes a case for expanding our focus from national-attribute studies of intranational conflict toward strategic behavior studies of intranational conflict. One payoff of such a move is that it enables us to specify a linkage between the strategic behavior of both domestic and international actors and thus address the often theorized, but rarely established, intranational-international conflict nexus. Further, the author takes a synthetic approach to the recent debate between action-reaction and rational expectations models of international conflict behavior and derives hypotheses concerning the behavior of both domestic and international parties to an armed intranational conflict. The hypotheses are then tested in a time-series case study design using the Rhodesian/Zimbabwean case for the period from 1957 to 1979. The results demonstrate that there existed an intranational-international conflict nexus in this case and highlight the utility of adopting a strategic behavior approach to studying armed intranational conflict.
In this article, the authors develop and empirically evaluate a general model of the linkages between domestic and international conflict behavior. Much of the literature on domestic international interactions has focused on the structural constraints of the international and domestic systems on leaders' foreign policy decisions. Rather than focusing on structural constraints, the present authors model the influence of the behavior of domestic and international rivals on leader decision making. The impact of rivals' behavior on conflict across the domestic-international nexus has been neglected relative to the role of structural factors. This study helps redress that imbalance. The authors test their model with a statistical analysis of Zaire during the period 1975 to 1992 and find substantial support for the model.
Most efforts in international relations scholarship focus on understanding war and conflict. To the extent that peace is considered, it is often treated as an afterthought or a control condition. In this paper, we construct a five-level scale of dyadic peace. We then operationalize the scale using indicators suggested by different scholarly literatures as well as measures derived from case studies. Further, we advocate the use of “anchor cases” and pair-wise comparisons to code dyadic peace in non-rivalry periods. We conclude with a pilot study of the scale, as applied to pairs of states over the period From 1816 to 2006.
This study posits a theory to explain government and dissident sequential responses to one another and develops a statistical model to test the implied hypotheses. While competing hypotheses emerge from both formal and empirical models, the current literature lacks a single, coherent, theoretical, and empirically corroborated model of the interactive relationship between dissident and government behavior. The study seeks to fill this lacuna in the literature by developing a comprehensive theory to account for a large number of competing hypotheses within a single framework. The subsequent empirical tests enable one to find support for the various competing hypotheses under different sets of conditions. The analyses of Chile (1983—1992) and Venezuela (1987— 1992) provide evidence that the model captures well the sequential responses of Chilean and Venezuelan governments and dissidents.
From as early as the Roman Empire to the present day, governments have grappled with how best to respond to political violence from organized insurgent groups. In response to insurgent groups, some governments have emphasized a direct military response or what is often called ‘attrition’. Other states have stressed a softer, political strategy or what is often called the ‘hearts and minds’ approach. Either approach places the population at the center of a struggle between the government and violent dissidents. Despite numerous works emphasizing either ‘attrition’ or ‘hearts and minds’, few theoretical studies have attempted to compare their relative success. Using an agent-based computational model, we examine which approach is more successful at quelling insurgencies and find that a hearts and minds approach is superior to an attrition strategy. We illustrate the model with insights from the Iraqi insurgency and, more generally, the model has implications for other insurgencies, such as in Chechnya.
Elisabeth Wood's account of insurgent collective action in El Salvador is based on oral histories gathered from peasants who supported the insurgency and those who did not, as well as on interviews with military commanders from both sides. She explains how widespread support among rural people for the leftist insurgency during the civil war in El Salvador challenges conventional interpretations of collective action. Those who supplied tortillas, information, and other aid to guerillas took mortal risks and yet stood to gain no more than those who did not.
Aggregate data studies of domestic political conflict have used an Action-Reaction (AR) model that has produced contradictory findings about the repression/dissent nexus: Repression by regimes may either increase or decrease dissent by opposition groups. To clarify these findings I propose an alternative Rational Actor (RA) model from which are derived three propositions. (1) An increase in a government's repression of nonviolence will reduce the nonviolent activities of an opposition group but increase its violent activities. (2) The balance of effects, that is, whether an increase in the regime's repression increases or decreases the opposition group's total dissident activities, depends upon the government's accommodative policy to the group. (3) Consistent government accommodative and repressive policies reduce dissent; inconsistent policies increase dissent. The RA model thus accounts for the contradictory findings produced by the AR-based aggregate data studies of repression and dissent.
Propositions about determinants of political violence at the cross-national level are derived from rational action theory and tested across the entire population of independent states in the mid-1970s. The data support two rational action hypotheses: Rates of domestic political violence are higher at intermediate levels of both regime repressiveness and negative sanctions than at either low or high levels of these indicators of institutionalized and behavioral coercion. Two hypotheses that can be interpreted within either a rational action or a deprivation framework also are supported: High rates of economic growth reduce the incidence of political violence, and potential separatism increases the incidence of violence. A deprivation hypothesis that high life expectancy reduces the incidence of political violence is not supported. Overall, this set of findings favors a rational action rather than a deprivation approach to explaining why nations differ in rates of political violence.
By analytically decoupling war and violence, this book explores the causes and dynamics of violence in civil war. Against the prevailing view that such violence is an instance of impenetrable madness, the book demonstrates that there is logic to it and that it has much less to do with collective emotions, ideologies, and cultures than currently believed. Kalyvas specifies a novel theory of selective violence: it is jointly produced by political actors seeking information and individual civilians trying to avoid the worst but also grabbing what opportunities their predicament affords them. Violence, he finds, is never a simple reflection of the optimal strategy of its users; its profoundly interactive character defeats simple maximization logics while producing surprising outcomes, such as relative nonviolence in the 'frontlines' of civil war.
The problem of aggregating WEIS events data, coded as discrete events, into a continuous time series representing conflict or cooperation between two nations is discussed. Past literature on the subject reveals continuing confusion and controversy regarding such a conflict-cooperation scale. A new scale based on a small panel of international relations faculty is presented. Replication of several past studies of great power reciprocity, using the new scale, shows a slight increase in the statistical significance of relationships.
Suicide terrorism is rising around the world, but the most common explanations do not help us understand why. Religious fanaticism does not explain why the world leader in suicide terrorism is the Tamil Tigers in Sri Lanka, a group that adheres to a Marxist/Leninist ideology, while existing psychological explanations have been contradicted by the widening range of socio-economic backgrounds of suicide terrorists. To advance our understanding of this growing phenomenon, this study collects the universe of suicide terrorist attacks worldwide from 1980 to 2001, 188 in all. In contrast to the existing explanations, this study shows that suicide terrorism follows a strategic logic, one specifically designed to coerce modern liberal democracies to make significant territorial concessions. Moreover, over the past two decades, suicide terrorism has been rising largely because terrorists have learned that it pays. Suicide terrorists sought to compel American and French military forces to abandon Lebanon in 1983, Israeli forces to leave Lebanon in 1985, Israeli forces to quit the Gaza Strip and the West Bank in 1994 and 1995, the Sri Lankan government to create an independent Tamil state from 1990 on, and the Turkish government to grant autonomy to the Kurds in the late 1990s. In all but the case of Turkey, the terrorist political cause made more gains after the resort to suicide operations than it had before. Thus, Western democracies should pursue policies that teach terrorists that the lesson of the 1980s and 1990s no longer holds, policies which in practice may have more to do with improving homeland security than with offensive military action.
The terms terror, terrorism, and terrorist do not identify causally coherent and distinct social phenomena but strategies that recur across a wide variety of actors and political situations. Social scientists who reify the terms confuse themselves and render a disservice to public discussion. The U.S. government's own catalogs of terrorist events actually support both claims.
While some of the intrastate war literature calls for the disaggregation of civil conflict, most of those studies focus on the geography of civil conflict failing to take into account the various actors involved in such conflicts. This study addresses the multi-actor nature of civil conflict by examining whether 'actor aggregation' affects the inferences drawn from quantitative studies of civil conflict. Using two cases, Cambodia (1980-2004) and Indonesia (1980-2004), the authors examine how multiple dissident groups' behavior aggregated together can affect the inferences drawn from quantitative studies of government-dissident interactions. The results demonstrate that researchers may draw different inferences and commit both Type I and Type II errors using different actor aggregations. The results have myriad implications for the study of civil conflict and conflict processes.
Rebuilding social and economic order in conflict and post-conflict areas will be critical for the United States and allied governments for the foreseeable future. Little empirical research has evaluated where, when, and how improving material conditions in conflict zones enhances social and economic order. We address this lacuna, developing and testing a theory of insurgency. Following the informal literature and US military doctrine, we model insurgency as a three-way contest between rebels seeking political change through violence, a government seeking to minimize violence through some combination of service provision and hard counterinsurgency, and civilians deciding whether to share information about insurgents with government forces. We test the model using new data from the Iraq war. We combine a geo-spatial indicator of violence against Coalition and Iraqi forces (SIGACTs), reconstruction spending, and community characteristics including measures of social cohesion, sectarian status, socio-economic grievances, and natural resource endowments. Our results support the theory's predictions: counterinsurgents are most generous with government services in locations where they expect violence; improved service provision has reduced insurgent violence since the summer of 2007; and the violence-reducing effect of service provision varies predictably across communities.
This paper models the early dynamics of insurgency using an agent-based computer simulation of civilians, insurgents, and soldiers. In the simulation, insurgents choose to attack government forces, which then strike back. Such government counterattacks may result in the capture or killing of insurgents, may make nearby civilians afraid to become insurgents, but may also increase the anger of surrounding civilians if there is significant collateral damage. If civilians become angry enough, they become new insurgents. I simulate the dynamics of these interactions, focusing on the effectiveness of government forces at capturing insurgents vs. their accuracy in avoiding collateral damage. The simulations suggest that accuracy (avoidance of collateral damage) is more important for the long-term defeat of insurgency than is effectiveness at capturing insurgents in any given counterattack. There also may be a critical 'tipping point' for accuracy below which the length of insurgencies increases dramatically. The dynamics of how insurgencies grow or decline in response to various combinations of government accuracy and effectiveness illustrate the tradeoffs faced by governments in dealing with the early stages of an insurgency.
The author derives the generating mechanism of a temporally aggregated process when the disaggregated one belongs to the vector autoregressive integrated moving average class. He then studies the effects of temporal aggregation on a set of characteristics of usual interest such as exogeneity, causality, cointegration, and common features. An empirical example with Canadian interest rates illustrates the main issues.
State of the practice and art in sentiment analysis
- M Shellman Stephen
- Covington Michael
- Zangrilli Marcia
Nickel & DIMEing the adversary: Does it work or PMESII them off? Presented at the annual meeting of the International Studies Association
- D Horne Cale
- Shellman Stephen
- Stewart Brandon
Fair & balanced or fit to print: The effects of source bias on event data analysis. Paper presented at the annual meeting of the International Studies Association
- Reeves Andrew
- Shellman Stephen
- Stewart Brandon