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What explains the type of electoral campaign run by political parties? We provide a new perspective on campaigns by focusing on the strategic use of emotive language. We argue that the level of positive sentiment parties adopt in their campaigns depends on their incumbency status, their policy position, and objective economic conditions. We test th...
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Citations
... At the current level, previous manifesto research related to sentiment/emotion analysis revolves around various European parities' campaign materials [Crabtree et al., 2018, Jentsch et al., 2021, Koljonen et al., 2022, of which many show evidence that the party's status in government and ideological positioning have a standing influence on these issues. Based on these findings, the study establishes two hypotheses (H) as follows: ...
... Hypothesis 1 (H1): The frequency of positive emotions will be highest in the incumbent party's manifesto than the opposition, while the frequency of negative emotions will be highest in the opposition party's manifesto than the incumbent A study conducted in campaign materials (including manifestos) across European elections indicates a correlation between the usage of emotions and the party's current status in government [Crabtree et al., 2018]. To be exact, the party or parties who are part of the incumbent government increase the frequency of positive emotions across different campaign materials than the opposition. ...
... To be exact, the party or parties who are part of the incumbent government increase the frequency of positive emotions across different campaign materials than the opposition. Regarding coalition governments, the party that controls the Prime Minister's position uses positive emotions more than its coalition partners [Crabtree et al., 2018]. The reason incumbent parties, especially those that control the PM office, increasingly assert more positive language. ...
The study involved the analysis of emotion-associated language in the UK
Conservative and Labour party general election manifestos between 2000 to 2019.
While previous research have shown a general correlation between ideological
positioning and overlap of public policies, there are still conflicting results
in matters of sentiments in such manifestos. Using new data, we present how
valence level can be swayed by party status within government with incumbent
parties presenting a higher frequency in positive emotion-associated words
while negative emotion-associated words are more prevalent in opposition
parties. We also demonstrate that parties with ideological similitude use
positive language prominently further adding to the literature on the
relationship between sentiments and party status.
... However, these studies have stopped short of examining the stylistic and rhetorical strategies that parties use to communicate their positions digitally through the stream of abbreviated messages on Twitter. In their study of European political party campaigns, Crabtree et al. (2018) note, "[w]hereas campaign content and campaign focus address what parties say and who they say it about, campaign sentiment addresses how they say it" (Crabtree et al. 2018, 1). A focus on rhetoric and style enables this study to address the inter-related nature of political language and affective sentiment and the ways in which they are used together to inform and persuade potential voters. ...
This article studies the communication strategies used in campaign messaging on Twitter by Spanish political parties during Spain’s 2019 General Elections in order to gauge whether a quantifiable relationship can be established between the style and rhetoric of a party’s Twitter speech, political platform, and political ideology. The analysis focuses on the discursive and rhetorical tactics that surround the parties’ engagement with issues of gender and feminism, particularly pressing concerns during this election cycle due to increased attention to gender-based violence and the organizing of feminist strikes in March 2019. In response to methodological questions surrounding the study of online speech, the study uses a combination of quantitative and qualitative methods to evaluate word choice, positive and negative sentiment, and use of platform infrastructure such as hashtags. Applying Natural Language Processing (NLP) techniques, the article examines word frequency, co-occurrence of qualified nouns, and sentiment analyses of tweets published by the five largest political parties in Spain between March 1 and May 15, 2019. Based on topic modelling, this corpus of tweets was then narrowed to those concerning gender and feminism and a close reading was conducted in order to locate the tweet’s ideological and discursive messaging within Spain’s sociopolitical context. Although word frequency analysis demonstrated that gender remained a concern for all five parties, noun co-occurrence and sentiment analysis revealed significant differences in how all parties engaged with gender as a political issue via their choices in rhetoric and style, which were linked to their platform and ideology via quantifiable measurements and qualitative close readings. As such, the study is able to conclude that using a combination of quantitative and qualitative methods enables researchers to draw nuanced and contextualized connections between the rhetoric and style of online political speech and the position of a political party on a given issue.Cet article étudie les stratégies de communicationemployées dans les messages publiés sur Twitter par les partis politiques espagnols durant les Élections générales espagnoles de l’année 2019 afin d’estimer si une relation quantifiable peut être établie entre le style et rhétorique d’un discours sur Twitter, d’un programme politique et d’une idéologie politique d’un parti. L’analyse est axée sur les tactiques discursives et rhétoriques qui sont autour de l’engagement des partis avec des questions du genre et du féminisme, étant des préoccupations particulièrement importantes pendant ce cycle d’élection à cause de l’attention augmentée à la violence liée au genre, ainsi qu’à l’organisation des grèves féministes en mars 2019. Considérant des questions méthodologiques concernant l’analyse du discours su rInternet, cette étude se sert d’une combinaison de méthodes quantitatives et qualitatives pour évaluer le choix des mots, l’opinion positive et négative et l’usage de l’infrastructure de plateforme, tel que les hashtags. En appliquant les techniques du Traitement automatique du langage naturel (TALN), cet article examine la fréquence de mots, la concomitance de noms qualifiés et les analyses de sentiments de tweets publiés par les cinq plus grands partis politiques en Espagne entre le 1ermars et le 15 mai 2019. Basé sur une modélisation de thèmes, ce corpus de tweets a ensuite été limité aux tweets concernant le genre et le féminisme. Une lecture attentive a ensuite été réalisée dans le but d’identifier les messages idéologiques et discursifs des tweets dans le contexte sociopolitique espagnol. Bien que l’analyse de la fréquence de mots ait démontré que le genre demeurait préoccupant pour tous les cinq partis, la concomitance de noms et l’analyse de sentiments ont révélé des différences significatives dans la façon dont les partis traitaient le genre comme question politique à travers leurs choix de style et de rhétorique, qui ont été liés à leur plateforme et à leur idéologie par le biais de mesures quantifiables et de lectures attentives qualitatives. Cette étude peut ainsi montrer que l’usage d’une combinaison de méthodes quantitatives et qualitatives permet aux chercheurs d’établir des liens nuancés et contextualisés entre le style et rhétorique du discours politique en ligne, ainsi que la position d’un parti politique en ce qui concerne une question donnée.
... The focus on voters' own responses in the present study is rather unique: so far, the materials that are the focus in related studies are usually party manifestos, press releases or related materials (Klüver and Sagarzazu, 2016;Crabtree et al., 2018). When leaders are the focus, the current trend is survey experiments where leader qualities are experimentally manipulated (see for example Tavares et al., 2018). ...
We propose that leaders play a more important role in voters’ party sympathy in proportional representation systems (PR) than previous research has suggested. Voters, from the 2018 Swedish General Election, were in an experiment asked to describe leaders and parties with three indicative keywords. Statistical models were conducted on these text data to predict their vote choice. The results show that despite that the voters vote for a party, the descriptions of leaders predicted vote choice to a similar extent as descriptions of parties. However, the order of the questions mattered, so that the first questions were more predictive than the second question. These analyses indicate that voters tend to conflate characteristics of leaders with their parties during election campaigns, and that leaders are a more important aspect of voting under PR than previous literature has suggested. Overall, this suggests that statistical analysis of words sheds new light of underlying sympathies related to voting.
... Another insight into intra-party politics possibly yielded by sentiment analysis is that speeches with strong negative emotions by members of the party could give us indications that, internally, the party is calling for a change. We demonstrate below how to apply sentiment analysis and explore between-party and overtime differences in the use of sentiment in party leader speeches (for examples of sentiment analysis applied to election manifestos or legislative speeches see Crabtree et al., 2018;Kosmidis et al., 2018 andRheault et al., 2016). ...
... Large parties, and parties in government, use more positive emotions than negative emotions. The latter finding is in line with other work using sentiment analysis on legislative speeches and election manifestos (Crabtree et al., 2018;Kosmidis et al., 2018;Rheault et al., 2016). Party leaders use more negativity and more arousal in their speeches compared to speeches by party chairpersons, MPs and ministers. ...
... Left-right ideology (relative and absolute) has inconsistent effects across the models. Surprisingly, unlike Crabtree et al. (2018), we do not find that moderate parties use more positive emotions in their speeches. Finally, unlike Rheault et al. (2016) we do not find a strong increase in the use of positive sentiment over time. ...
We present a new dataset of speeches given by Danish and Dutch politicians at party congresses between 1946 and 2017. The dataset is a unique collection of materials from different party archives and digital repositories. It offers a unique opportunity to analyse the issues discussed in these speeches, the positions taken and the rhetoric used by party elites over time and between countries. We describe the data and illustrate them with one application: a sentiment analysis that describes differences between parties and over time.
This study analyses the role of the main Spanish political groups in the polarisation of public opinion and the promotion of the culture of disinformation through Twitter (now Platform X). The study carries out an analysis of issues associated with tweets and retweets in Spanish of the total published (n = 33,506 messages out of a total of 49,288 messages), which are contrasted with 2,730 disinformation publications identified by the two most relevant fact-checking projects in Spain (Maldita.es and Newtral.es). Based on the applied methodology, a political-communicative context is observed on Platform X characterised by a high level of self-promotion and polarisation, facilitated by the communication strategy of specific topics, applied by the actors analysed. The results show how these political actors can play an active and differentiated role in the promotion of disinformation content identified by the Maldita.es and Newtral.es data verification projects. This may contribute to the polarisation of Spanish public opinion on Platform X by delegitimising the opinions of their opponents on issues of interest to the public.
Quantitative text analysis is a growing research field in political science, whereas very few combine survey experiments with in-depth analysis of citizens’ word expressions. This chapter illustrates how a survey experiment and a latent semantic analysis are successfully combined in analyzing the 2016 EU referendum in Great Britain (Brexit). This example combines an analysis of semantic cluster approach based on experimental text data with multivariate maximum likelihood estimations. Using this approach, we are able to make finer inferences on the relationship between threat conditions and individual political behavior.
