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Comparing Online Posting Typologies among Violent and Nonviolent Right-Wing Extremists

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Although many researchers, practitioners, and policymakers are concerned about identifying and characterizing online posting patterns of violent extremists prior to their engagement in violence offline, little is empirically known about their online patterns generally or differences in their patterns compared to their non-violent counterpart particularly. In this study, we drew from a unique sample of violent and non-violent right-wing extremists to develop and compare their online posting typologies (i.e., super-posters, committed, engaged, dabblers, and non-posters) in the largest white supremacy web-forum. We identified several noteworthy posting patterns that may assist law enforcement and intelligence agencies in identifying credible threats online.
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Comparing Online Posting Typologies among Violent and Nonviolent Right-Wing
Extremists
Ryan Scrivens
School of Criminal Justice, Michigan State University
East Lansing, Michigan, USA
rscriv@msu.edu
Garth Davies
School of Criminology, Simon Fraser University
Burnaby, British Columbia, Canada
Tiana Gaudette
School of Criminal Justice, Michigan State University
East Lansing, Michigan, USA
Richard Frank
School of Criminology, Simon Fraser University
Burnaby, British Columbia, Canada
Disclosure Statement
No potential conflict of interest was reported by the authors.
COMPARING ONLINE POSTING TYPOLOGIES
2
Comparing Online Posting Typologies among Violent and Nonviolent Right-Wing
Extremists
Abstract
Although many researchers, practitioners, and policymakers are concerned about identifying and
characterizing online posting patterns of violent extremists prior to their engagement in violence
offline, little is empirically known about their online patterns generally or differences in their
patterns compared to their non-violent counterpart particularly. In this study, we drew from a
unique sample of violent and non-violent right-wing extremists to develop and compare their
online posting typologies (i.e., super-posters, committed, engaged, dabblers, and non-posters) in
the largest white supremacy web-forum. We identified several noteworthy posting patterns that
may assist law enforcement and intelligence agencies in identifying credible threats online.
Purpose
This study examines typologies of posting behavior among violent and non-violent right-wing
extremists (RWEs) within a sub-forum of the largest white supremacy web-forum, Stormfront.
We expand our prior research on the online behaviors of violent and non-violent RWEs
1
by
developing and examining posting typologies that characterize the extremist posting behaviors of
each of the two user groups. This study represents an original contribution to the academic
literature on violent online political extremism on three key fronts.
First, the role of the Internet in facilitating violent extremism and terrorism continues to
be a primary concern for many researchers, practitioners, and policymakers
2
, with questions
often surrounding the impact of the offenders’ consumption of and networking around violent
COMPARING ONLINE POSTING TYPOLOGIES
3
extremist online content in their acceptance of extremist ideology and/or their decision to engage
in violent extremism and terrorism.
3
While increased attention has been given to detecting
violent extremists online prior to their engagement in violence offline and examining their digital
footprint,
4
few empirically grounded analyses have addressed this area of work. What little
evidence does exist suggests that practitioners and policymakers should not conceive violent
extremism as an offline versus online dichotomy. Gill and Corner
5
, for example, in their
assessment of the behavioral underpinnings of a sample of 119 lone-actor terrorists in the United
States (U.S.) and Europe found that the growth in the Internet altered lone-actors’ means of
radicalization and attack learning. Gill and colleagues
6
in their examination of the online
behaviors of 223 convicted United Kingdom (U.K.)-based terrorists similarly found that those
who learned online were more likely than those who did not learn online to network and interact
offline. Holbrook and Taylor
7
examined pre-arrest media usage of five case studies of U.K.-
based terrorists and found that subjects consumed a range of media across various platforms as
well as interacted both on- and offline. Lastly, Gaudette and colleagues
8
during their interviews
with Canadian former violent RWEs identified an important interaction between their on- and
offline behaviors during their involvement in violent extremism which were intertwined with
their extremist activities, identities, and a need for security. These efforts notwithstanding, this
emerging evidence remains in its infancy and requires further exploration.
Second, researchers, practitioners, and policymakers have paid close attention to the
presence of violent extremists and terrorists online in recent years, with a particular emphasis on
the digital patterns and behaviors of the extreme right.
9
This is largely the result of ongoing
reports that some violent RWEs and terrorists were active online prior to their attacks.
10
One of
the most recent examples is that of 28-year-old Australian Brenton Tarrant who, before killing
COMPARING ONLINE POSTING TYPOLOGIES
4
51 people in two Christchurch, New Zealand mosques in 2019 and live-streaming his attack,
announced his intentions on 8chan and produced a ‘manifesto’ linked on the website.
11
Similarly,
Payton Gendron, 18, posted details of his plan to attack the Tops Friendly Markets store in
Buffalo, NY in a private Discord chat room prior to killing 10 people as well as live-streamed
parts of his attack on Twitch and allegedly wrote and posted a 180-page manifesto on 4chan.
12
It
should come as little surprise that researchers have focused on the activities of RWEs on various
platforms, including on websites and discussion forums,
13
mainstream social media sites such as
Facebook,
14
Twitter,
15
and YouTube,
16
fringe platforms including 4chan
17
and Gab,
18
and digital
applications such as TikTok
19
and Telegram.
20
But most studies, similar to research on the causes
of violent extremism and terrorism in general, lack comparison groups, despite an urgent need to
focus on comparative analyses and consider how violent extremists are different than non-violent
extremists.
21
In other words, empirical research has overlooked differences in the online patterns
of those who share extreme ideological beliefs but are violent or non-violent offline.
22
Few
empirical studies have investigated online behaviors of violent and non-violent extremists. Holt
and colleagues
23
examined the underlying theoretical assumptions evident in radicalization
models through a case-study analysis of violent and non-violent extremists. Wolfowicz and
colleagues
24
used a matched case-control design to differentiate between terrorists and non-
violent radicals based on their social media profiles. Scrivens and colleagues
25
examined the
posting behaviors of violent and non-violent RWEs and whether specific posting behaviors were
characteristic of users’ violence status. Davies and colleagues
26
examined how violent and non-
violent RWE identities take shape over time online. Scrivens and colleagues
27
explored how
violent and non-violent RWEs’ time of entry into the lifespan of an extremist online community
and posting activity predicted their violence status. Lastly, Scrivens
28
quantified the existence of
COMPARING ONLINE POSTING TYPOLOGIES
5
extremist ideologies, personal grievances, and violent extremist mobilization efforts expressed
by a sample of violent and non-violent RWEs as well as a sample of postings within an extremist
online community. Despite these foundational studies, there remains a need to closely examine
the online patterns of violent extremists to inform future risk factor frameworks used by law
enforcement and intelligence agencies to identify credible threats online.
29
The current study
expands on this research
30
by examining the online posting typologies of violent and non-violent
posters.
Third, it has become increasingly common in the academic literature on violent online
political extremism to evaluate the development of extremist content online
31
or assess the levels
of – or propensity towards – violent radicalization online.
32
But far less is empirically known
about the posting patterns that make up these extremist spaces in general,
33
or the posting
typologies of those active in these spaces in particular.
34
What is known comes from just a
handful of empirical studies. To illustrate, Berger and Morgan
35
examined a sample of ISIS-
supporting Twitter accounts and uncovered a small of group of users who were the most active
and influential in the online networks. Ducol,
36
in his assessment of a French “Jihadosphere”
community, similarly uncovered a small group of active members who drove the flow of online
discussions – particularly the jihadi content. Similar patterns have been uncovered in other
empirical studies, including by Baele and colleague,
37
who identified a handful of “hyperactive”
posters in an Incel forum as well as by Shrestha and colleagues,
38
who found a group of active
users in a Swedish far-right forum who were influential in generating online discussion. Most
recently, Scrivens
39
identified several sub-types of super-poster profiles within sub-forum of
Stormfront.org, the largest collective RWE forums for a general audience, which included high-
intensity posters, high-frequency posters, and high-duration posters. Kleinberg and colleagues
40
COMPARING ONLINE POSTING TYPOLOGIES
6
measured the development of user activity and extremist language in Stormfront and found a
group of super users who accounted for most of the posts and extremist language. Scrivens and
colleagues
41
similarly found a small group of super-posters driving the high-posting activity in
two violent RWE forums, Iron March and Fascist Forge. In light of these important
contributions, more research is needed to examine the posting typologies of active users in these
extremist spaces – and not simply focus on the online patterns of super-posters, as has been the
case in this area of research. Further, research in this space has yet to identify differences in
posting typologies of those who share extreme ideological beliefs but are violent or non-violent
in the offline world. This is an important oversight for at least two reasons. First, much of the
current thinking about the relationship between online posting activity and extremist violence
seems to be premised on the untested assumption that more posting equals more violence. While
this presumption is intuitively appealing, it is not grounded empirically. Relatedly, practitioners
and policymakers continue to struggle with the size and scope of the potential online violent
extremist threat.
42
In attempting to quantify and assess the distinction in posting behavior
between violent and non-violent users, this research aims to assist practitioners and policy
makers in their critical efforts to identify credible online threats.
Current Study
Data and Sample
We analyzed all open access content made by a sample of violent and non-violent RWEs in a
Canadian-themed sub-forum of Stormfront, which is the oldest and largest racial hate site and
one of the most influential RWE forums in the world.
43
Stormfront is made up of an array of
sub-sections addressing a variety of topics, including an ‘International’ section composed of a
COMPARING ONLINE POSTING TYPOLOGIES
7
range of geographically and linguistically bounded sub-forums (e.g., Stormfront Europe,
Stormfront Downunder, and Stormfront Canada). Importantly, Stormfront has served as a
“funnel site” wherein forum users have been recruited by other RWE users into violent offline
groups (e.g., the Blood & Honour, Hammerskins, and various Ku Klux Klan branches).
44
Today,
Stormfront has approximately 367,000 ‘members’ and contains over 14 million posts.
Although a number of emerging digital spaces have been adopted by RWEs in recent
years, Stormfront has been the focus of much research attention since its inception and continues
to be a valuable online space for researchers to assess behavioral posting patterns. To illustrate,
researchers have assessed recruitment efforts made by forum users,
45
the formation of a virtual
community
46
and collective identity,
47
the extent to which the site is connected to other racial
hate sites
48
, and how discourse on the site is less virulent and more palatable to readers.
49
Most
recently, researchers have examined RWE posting behaviors found on the platform,
50
the
development of user activity and extremist language there
51
, the impact of presidential election
results on Stormfront posting behaviors
52
, and the ways in which the collective identity of the
extreme right takes shape over time
53
and is affected by offline intergroup conflict on the
forum.
54
Some exploratory work has also compared the developmental posting behaviors of
violent and non-violent users on Stormfront.
55
However, few studies have identified differences
in posting patterns of Stormfront users who share extreme ideological beliefs but are violent or
non-violent in the offline world
56
and even fewer studies have examined posting typologies of
these two user types. The current study expands on prior research that differentiates the posting
behaviors of violent and non-violent RWEs.
57
Data collection and sampling efforts proceeded in two stages. First, a custom-written
computer program that was designed to collect vast amounts of information online captured all
COMPARING ONLINE POSTING TYPOLOGIES
8
open-source content on Stormfront Canada,
58
which resulted in approximately 125,000 sub-
forum posts made by approximately 7,000 authors between September 12, 2001 and October 29,
2017.
59
Second, to pinpoint users in the sub-forum who were violent or non-violent RWEs
offline, a former violent extremist
60
voluntarily reviewed a list of 7,000 users who posted in the
sub-forum and selected those who matched one of the two user types.
61
As a result, a total of 50
violent and 50 non-violent RWEs were identified from the list of usernames and their content
was then isolated from the collected sub-forum data: 12,617 posts from the violent users and
17,659 posts from the non-violent users.
62
Overall, the sample included 30,276 posts, with the
first post made on September 1, 2004 and the last post made on October 29, 2017.
Importantly, Stormfront Canada was selected because it was an online space that the
former extremist actively participated in during their involvement in violent RWE and was
intimately familiar with; that is, they were familiar with the users who posted there and could
identify individuals who they knew were violent or non-violent RWEs in the offline world. The
former who was actively involved in the North American RWE movement and a prominent
figure there for more than 10 years, both in recruitment and leadership roles – and primarily in
violent racist skinhead groups in Canada.
In an effort to verify the authenticity of each user identified by the former extremist, the
user identification process was done under the supervision of the lead researcher of this project.
Specifically, each time the former identified a user of interest, they were asked to explain in as
much detail possible why the user was identified as a violent or non-violent RWE. The former
was also asked to provide detailed examples of the activities that each user engaged in as well as
their association with or connection to each identified user. It is worth noting that no attempt was
made to have the informant familiar with each of the 7,000 users link them to their usernames,
COMPARING ONLINE POSTING TYPOLOGIES
9
but for those who were identified for the current study, to the best of our knowledge each of their
usernames represented a unique user. In particular, the informant reviewed a list of all sub-forum
users, and next to each they included the names of each identified user, thus documenting that
each username was distinct and there was no overlap among them – a sampling procedure
supported by previous studies.
63
We do, however, acknowledge that this single source may be
more familiar with the histories of some of the identified individuals than others. The informant
categorized individuals as violent if s/he had personally witnessed the violent activities, and/or
had direct first-hand-knowledge of said activities. We thus have strong confidence in the violent
categorization but have slightly less confidence in the non-violent categorization. It was possible
that an individual committed a violent act outside the informant’s presence, and that the
informant was never made aware of it. This may have biased the sample.
RWEs who were identified for the current study were actively involved in right-wing
extremism. In particular, they – like all extremists – structure their beliefs on the basis that the
success and survival of the in-group is inseparable from the negative acts of an out-group and, in
turn, they are willing to assume both an offensive and defensive stance in the name of the
success and survival of the in-group.
64
RWEs in the current study were therefore characterized as
those who subscribed to a racially, ethnically, and/or sexually defined nationalism, which is
typically framed in terms of white power and/or white identity (i.e., the in-group) that is
grounded in xenophobic and exclusionary understandings of the perceived threats posed by some
combination of non-whites, Jews, Muslims, immigrants, refugees, members of the LGBTQ+
community, and feminists (i.e., the out-group(s)).
65
Having said that, violent RWEs in the current
study committed several acts of known physical violence against a person, including violent
attacks against minorities and anti-racist groups. Violence in this regard aligns with Bjørgo and
COMPARING ONLINE POSTING TYPOLOGIES
10
Ravndal’s
66
conceptualization of RWE violence, which they define as “violent attacks whose
target selection is based on extreme-right beliefs and corresponding enemy categories—
immigrants, minorities, political opponents, or governments [...] [or] spontaneous violence.” On
the other hand, non-violent RWEs in the current study did not engage in physical violence
against a person in any known capacity but were actively involved in RWE activities offline,
including but indeed not limited to rallies, marches, protests, postering and flyering campaigns,
and group meetings and gatherings.
Keywords and Selection Procedure
To identify extremist content and, by extension, typologies of extremist posting behavior in the
sub-forum, the first step was to determine extremist topics found in the data that would be
measured. A list of keywords was therefore developed that accounted for discussions associated
with three primary adversary groups of the extreme right: (1) Jews, (2) Blacks, and, (3) lesbian,
gay, bisexual, transgender, and queer (LGBTQ+) communities. Research suggests that these
three adversary groups are widely discussed and demonized in RWE discussions forums,
67
among many other online platforms used by the extreme right. While by no means are these the
only adversary groups targeted by them, historically Jewish, Black and LGBTQ+ communities
have been the primary opponents of the RWE movement.
68
Jews, for example, have been subject
to extensive criticism by the extreme right. They have been labeled as “the source of all evil”,
“the spawn of the Devil himself”, conspiring to extinguish the white race and breeding them out
of existence – through “Jew-controlled” government, financial institutions, and media (i.e.,
Zionist Occupation Government (ZOG) conspiracy).
69
Black communities, too, have been the
primary target of much of the hateful sentiment expressed by the extreme right. Blacks have been
COMPARING ONLINE POSTING TYPOLOGIES
11
constructed as “mud races” and the descendants of animals created before Adam and Eve;
“savages” who viciously rape white women and take jobs away from white communities; and the
foot soldiers of “conspiring Jews”.
70
Adherents of this male-dominated movement have also
categorized anyone who is not heterosexual as “contaminated” and “impure”, not only by
maintaining that the gay rights movement is the killer of the traditional white family and the
cultural destruction of the white race, but that gays are responsible for the contemporary AIDS
endemic.
71
For each of the three adversary groups, a list of keywords was developed by drawing
from extensive lists of slur words found online. Each list included an equal number of words via
a standardization procedure: the frequency with which each keyword was found in the data and
the inflection point in the data were identified for each list, and the average inflection point was
calculated for each. Collectively, the average inflection point value was 42 keywords, and in turn
each list included 42 words that were randomly drawn from their associated list.
72
Typologies of Posting Groups
The next step was to develop typologies of posting frequency groups, which was done through a
multi-step process. First, the number posts, both (a) in total and (b) by each of three adversary
groups, were summed for each forum user in the sample. This created four aggregated variables:
the total number of posts, and the total number of posts related to Blacks, Jews, and the
LGBTQ+ community. Second, the mean and standard deviation was calculated for each of the
aggregate variables. Third, super-posters were defined as those users whose aggregate number of
posts was more than two standard deviations higher than the mean for that variable.
Theoretically, a forum user could be a super-poster in all four domains (i.e., total number of
COMPARING ONLINE POSTING TYPOLOGIES
12
posts as well as each of the three adversary groups). In practice, this procedure identified six
super-posters. Four of these users were, in fact, super-posters across each of the four domains,
while one user was only a super-poster in one domain, and the other was a super-poster in two
domains. Fourth, at the other end of the spectrum, a separate category for non-posters was
created. Certainly, every forum user in the sample had to have at least one post, otherwise they
would not be in the sample. But not all users made posts in relation to each of the adversary
groups. For example, 24% of users did not post any comments related to Blacks. Similarly, 37%
of users made no posts about Jews, and 46% percent posted no comments referencing the
LGBTQ+ community. In fact, fewer than half of all users posted content associated with all three
adversary groups. Fifth, dabblers were identified as users who, in relation to each domain, posted
between one and nine times. Finally, the engaged and committed categories were created by
equally dividing up the remaining forum users. This process was used to reflect the fact that the
actual number of posts per domain varied noticeably. In sum, each of the groups is defined as
follows:
1. Non-posters – 0 posts
2. Dabblers – 1 to 9 posts
3. Engaged – lower half of range between 10 and
𝑥"
#± 2 SD posts
4. Committed – upper half of range between 10 and
𝑥"
#± 2 SD posts
5. Super-posters – over
𝑥"
#+ 2 SD posts
Sentiment Analysis
In addition to constructing typologies based on posting frequency, we sought to assess the
relationship between these typologies and their emotive content. In other words, we wanted to
COMPARING ONLINE POSTING TYPOLOGIES
13
determine whether there are differences in how violent and non-violent users communicate their
attitudes and opinions about their adversaries to the wider online community. Thus, the context
surrounding each of the abovementioned keywords was systematically evaluated using sentiment
analysis software. Also known as ‘opinion mining’, sentiment analysis is a data collection and
analytic method that allows for the application of subjective labels and classifications. It can
evaluate the opinions of individuals by organizing data into distinct classes and sections,
assigning an individual’s sentiment with a polarity score (i.e., a positive, negative, or neutral
score).
73
SentiStrength, which is an established sentiment analysis program that has been widely
used by criminologists in terrorism and extremism studies,
74
was utilized for the current study, as
it allows for a systematic analysis of a user’s discussion that could be considered ‘extreme’ in
online settings.
75
To illustrate, it allows for a keyword-focused method of determining sentiment
near a specified keyword.
76
Equally important is another key feature of SentiStrength: polarity
scores are augmented by characters that can influence scores assigned to the text, such as active
and powerful language, booster words, negative words, repeated letters, repeated negative terms,
antagonistic words, punctuation, and other distinctive characters suited for studying an online
context. In theory, the higher a polarity score is assigned to a piece of text, the more likely the
text includes intense opinions.
77
Results
The results are divided into three sections: (1) a comparison of the online posting typologies
based on posting frequencies (i.e., super-posters, committed, engaged, dabblers, and non-
posters); (2) a comparison of the online posting typologies based on posting frequencies
COMPARING ONLINE POSTING TYPOLOGIES
14
targeting adversary groups (i.e., Black, Jewish, and LGBTQ+ communities), herein referred to as
“adversary posting typologies”; and, (3) a comparison of the sentiment expressed by each
adversary posting typology. Analyses were conducted within and across sample groups (i.e., the
violent users and the non-violent users).
Posting Typologies
Table 1 presents the online posting typology by sample group, which shows interesting patterns
in posting frequencies observed within and across samples. In particular, for the non-violent
sample, the fewest number of these users made up the super-posters (n = 4) compared to the
number of non-violent users comprising the committed posters (n = 14), the engaged posters (n =
18), and the dabbler posters (n = 14). Similarly, the fewest number of violent users made up the
super-posters (n = 2) compared to the number of violent users comprising the committed posters
(n = 16), the engaged posters (n = 11), and the dabbler posters (n = 21). Nonetheless, one notable
difference across sample groups was that fewer non-violent users fell into the dabblers posting
typology compared to violent users (14 users and 21 users, respectively) and instead a noticeably
larger proportion of non-violent users made up the engaged posting typology than their violent
counterpart (18 users and 11 users, respectively), as is illustrated in Figure 1.
Table 1. Posting typology by sample group.
Non-violent
Violent
Dabblers
14
21
Engaged
18
11
Committed
14
16
Super-posters
4
2
COMPARING ONLINE POSTING TYPOLOGIES
15
Figure 1. Posting typology by sample group.
In addition, the non-violent sample contained a slightly larger proportion of super-posters
than those observed in the violent sample (n = 4 and 2, respectively), but the non-violent sample
contained a relatively smaller proportion of committed posters than those in the violent sample (n
= 14 and 16, respectively). Conversely, the non-violent sample contained a noticeably larger
proportion of engaged posters than those in the violent sample (n = 18 and 11, respectively) but
the non-violent sample contained a much smaller proportion of dabbler posters than those
observed in the violent sample (n = 14 and 21, respectively).
Adversary Posting Typologies
A comparison of the adversary groups (anti-Black, anti-Semitic, and anti-LGBTQ+) within and
across sample groups yielded several interesting findings, with two obvious patterns emerging.
First, starting from the least active adversary typology category (i.e., the non-posters) to the most
active typology category (i.e., the super-posters), in general there was a gradual increase in the
frequency of users making up each. In other words, the rate at which non-violent and violent
14
18
14
4
21
11
16
2
Dabblers Engaged Committed Super-posters
Non-Violent Violent
COMPARING ONLINE POSTING TYPOLOGIES
16
users comprised the most active adversary group categories was noticeably less than the number
of users comprising the less activate adversary group categories. Figures 2 through 4 illustrate
this steady increase in user frequency by adversary and sample groups.
Figure 2. Anti-Black typology category by sample group.
Figure 3. Anti-Semitic typology category by sample group.
12
20
8
6
4
12
21
7
9
1
Non-posters Dabblers Engaged Committed Super-posters
Non-Violent Violent
17 17
67
3
20
17
6 6
1
Non-posters Dabblers Engaged Committed Super-posters
Non-Violent Violent
COMPARING ONLINE POSTING TYPOLOGIES
17
Figure 4. Anti-LGBTQ+ typology category by sample group.
Second, across all adversary groups, a larger proportion of super-posters were observed in the
non-violent sample than in its violent counterpart. Specifically, for the anti-Black group, a larger
proportion of super-posters were observed in the non-violent sample (n = 4) than those in the
violent group (n = 1). Similarly, both anti-Semitic and anti-LGBTQ+ groups consisted of a larger
proportion of non-violent super-posters than those in the violent sample (see Table 2).
Table 2. Posting typology by adversary group and sample group.
Non-violent
Anti-
Black
Anti-
Semitic
Anti-
LGBTQ+
Anti-
Black
Anti-
Semitic
Anti-
LGBTQ+
Non-posters
12
17
23
12
20
23
Dabblers
20
17
11
21
17
12
Engaged
8
6
7
7
6
8
Committed
6
7
6
9
6
6
Super-posters
4
3
3
1
1
1
There was also some variation in the number of non-violent and violent users comprising
the remaining adversary typology categories (i.e., the committed, engaged, dabbler, and non-
23
11
76
3
23
12
8
6
1
Non-posters Dabblers Engaged Committed Super-posters
Non-Violent Violent
COMPARING ONLINE POSTING TYPOLOGIES
18
posters), but in general these patterns were similar across samples. To illustrate, for the
committed posters in the anti-Black group, a smaller proportion of non-violent users (n = 6)
comprised this category than those in the violent sample (n = 9), but a similar proportion of non-
violent and violent users made up the anti-Semitic (n = 7 and 6, respectively) and anti-LGBTQ+
(n = 6 and 6, respectively) groups. For the engaged poster category, a similar proportion of non-
violent and violent users made up the anti-Black (n = 8 and 7, respectively), anti-Semitic (n = 6
and 6, respectively), and anti-LGBTQ+ (n = 7 and 8, respectively) groups. Likewise, a similar
proportion of non-violent and violent dabbler posters comprised the anti-Black (n = 20 and 21,
respectively), anti-Semitic (n = 17 and 17, respectively), and anti-LGBTQ+ (n = 11 and 12,
respectively) groups. Lastly, for the non-posters, a similar proportion of non-violent and violent
users made up the anti-Black (n = 12 and 12, respectively) and anti-LGBTQ+ (n = 23 and 23,
respectively) groups, but a smaller proportion of non-violent users (n = 17) comprised the anti-
Semitic group than those in the violent sample (n = 20).
Sentiment Expressed by Adversary Posting Typology
Table 3 provides a description of the sentiment expressed towards the three adversary groups,
both by sample and typology. From a macro-level perspective, several noteworthy patterns
emerged in the data. First, on average and across all typology categories, the non-violent users
posted messages about their adversaries that were more negative than those posted by the violent
sample.
COMPARING ONLINE POSTING TYPOLOGIES
19
Table 3. Average sentiment of posting typology by adversary group and sample group.
Non-violent
Anti-
Black
Anti-
Semitic
Anti-
LGBTQ+
Anti-
Black
Anti-
Semitic
Anti-
LGBTQ+
Dabblers
-0.34
-1.99
-1.36
-0.75
-1.62
-0.73
Engaged
-0.83
-3.02
-1.04
0.04
-1.53
-0.90
Committed
-0.74
-1.57
-1.52
-0.45
-1.80
-2.07
Super-posters
-1.36
-2.61
-2.24
-0.75
-1.63
-1.96
For example, the average sentiment scores for non-violent users about Jews (sentiment score = -
2.14), LGBTQ+s (sentiment score = -1.41), and Blacks (sentiment score = -0.61) was more
negative compared with the average sentiment scores for the violent users’ discussions about
Jews (sentiment score = -1.64), LGBTQ+s (sentiment score = -1.12) or Blacks (sentiment score
= -0.54). Nonetheless, a second pattern that emerged in the data was that, for both the non-
violent and violent sample groups, on average the scores for messages about Jews were the most
negative (sentiment score = -2.14 and -1.64, respectively) compared with posting scores for
users’ discussions about LGBTQs+ (sentiment score = -1.41 and -1.12, respectively) or Blacks
(sentiment score = -0.61 and -0.54, respectively). Figure 5 provides an illustration of these
patterns in the data.
COMPARING ONLINE POSTING TYPOLOGIES
20
Figure 5. Average sentiment of posting typology by adversary group and sample group.
A fine-grain analysis of the sentiment by adversary posting typology also revealed
several notable patterns in the data. First, on average the scores for the non-violent super-posters’
messages about Jews were the most negative (sentiment score = -2.61) compared with sentiment
scores for discussions about LGBTQ+s (sentiment score = -2.24) or Blacks (sentiment score = -
1.36). For the violent super-posters, on average the scores for their messages about LGBTQ+s
were the most negative (sentiment score = -1.96) compared with sentiment scores for discussions
about Jews (sentiment score = -1.63) or Blacks (sentiment score = -0.76). Interestingly though
was that the adversary sentiment that was expressed by non-violent super-posters was more
negative than that of the violent super-posters on average (sentiment score = -1.44 and -2.07,
respectively).
Second, similar to the sentiment expressed by the non-violent super-posters, the average
sentiment for the non-violent committed posters was the most negative for discussions about
-3.50
-3.00
-2.50
-2.00
-1.50
-1.00
-0.50
0.00
0.50
Dabblers Engaged Committed Super-posters
Anti-Black (Non-Violent) Anti-Semitic (Non-Violent) Anti-LGBTQ+ (Non-Violent)
Anti-Black (Violent) Anti-Semitic (Violent) Anti-LGBTQ+ (Violent)
COMPARING ONLINE POSTING TYPOLOGIES
21
Jews (sentiment score = -1.52) compared with sentiment for discussions about LGBTQ+s
(sentiment score = -1.52) or Blacks (sentiment score = -0.74). And similar to the sentiment
expressed by the violent super-posters, on average the scores for their messages about LGBTQ+s
were the most negative (sentiment score = -1.96) compared with scores for discussions about
Jews (sentiment score = -2.07) or Blacks (sentiment score = -0.45). However, unlike the
adversary sentiment expressed by both non-violent and violent super-posters, the sentiment
expressed by non-violent committed posters was less negative on average than that of the violent
committed posters (sentiment score = -1.44 and -1.28, respectively).
Third and similar to the sentiment expressed by the non-violent super-posters as well as
the non-violent committed posters, the average sentiment scores for the non-violent engaged
posters were the most negative for discussions about Jews (sentiment score = -3.02) compared
with sentiment for discussions about LGBTQ+s (sentiment score = -1.04) or Blacks (sentiment
score = -0.83). Yet the composition of the violent engaged posters differed from the violent
super-posters and committed posters. For the violent engaged posters, on average the scores for
their messages about Jews were the most negative (sentiment score = -1.80) compared with
scores for discussions about LGBTQ+s (sentiment score = -0.90) or Blacks (sentiment score =
0.04). Nonetheless, the adversary sentiment expressed by non-violent engaged posters was more
negative on average than that of the violent engaged posters (sentiment score = -0.08 and -1.63,
respectively) which was comparable to the composition of the super-posters.
Lastly, on average the scores for the non-violent dabbler posters’ messages about Jews
were the most negative (sentiment score = -1.99) compared with sentiment scores for discussions
about LGBTQ+s (sentiment score = -1.36) or Blacks (sentiment score = -0.34), which was
similar to the sentiment expressed by the non-violent super-posters, committed posters, and
COMPARING ONLINE POSTING TYPOLOGIES
22
engaged posters. Regardless, the composition of the violent dabbler posters differed from the
violent super-posters and committed posters but were comparable to the composition of the
violent engaged posters. That is, on average the scores for violent dabbler posters’ messages
about Jews were the most negative (sentiment score = -1.62) compared with scores for
discussions about Blacks (sentiment score = -0.75) or LGBTQ+ (sentiment score = -0.73). But
most importantly, the adversary group sentiment expressed by non-violent dabbler posters was
more negative on average than that of the violent dabbler posters (sentiment score = -1.03 and -
1.23, respectively) which was comparable to the composition of the super-posters and the
committed posters.
Discussion
This study focused on comparing online posting typologies among a unique sample of violent
and non-violent RWEs within the open-access sections of a sub-forum of Stormfront, which
expands our prior research on the online behaviors of violent and non-violent RWEs.
78
Several
conclusions can be drawn from this comparative analysis, which may lead to methods of
identifying credible threats online (i.e., potentially violent individuals).
First, super-posters made up a noticeably small proportion of users compared to all other
posting typology categories for both the violent and non-violent sample groups. In other words,
the fewest number of users comprised this posting category. This finding comes as little surprise,
given that previous research has overwhelmingly found that super-posters make up a very small
proportion of all posters in online spaces that facilitate extremism.
79
Yet research suggests that
these user types, whether in RWE online communities
80
or online communities in general,
81
tend
to dominate much of the online discussions and may be opinion leaders who influence the
COMPARING ONLINE POSTING TYPOLOGIES
23
attitudes, beliefs, motivations, and/or behaviors of others.
82
Perhaps it is the case that these
super-posters were the most influential posters in the sample, but this requires further
exploration. Having said that, the violent users in the current study consisted of a large
proportion of the least active posting typology (i.e., the dabbler posters) than their non-violent
counterpart, which again comes as little surprise given that recent work on the online behaviors
of RWEs found those who are actively involved in violent RWE activities offline tend to be
concerned that law enforcement officials and anti-racist groups are monitoring their online
activities and may modify their posting activities to avoid detection.
83
Empirical research
similarly suggests that violent members of RWE movements are largely clandestine, often
paranoid because of the violence they engage in, and for this reason are concerned about
revealing their identities.
84
With this in mind, it may be the case that the violent RWEs in the
current study were concerned that, by posting in an online space that can be publicly viewed,
they may be putting themselves in a vulnerable position and could become the subject of an
investigation from anti-hate watch-organizations or even law enforcement. This most likely had
an impact on the content that they posted on the site and the results of the study in general.
Nonetheless, a surprising finding in the current study was that the violent users comprised a
slightly larger proportion of committed posters than the non-violent users. This is an important
finding, as the committed posters were among the most active posting typology in the study.
Research suggests that the volume with which an individual communicates with members of a
particular group is associated with their level of social influence.
85
Perhaps the violent committed
posters were among most influential posters and opinion leaders in the sample based on their
online posting composition. Regardless, this requires further exploration.
COMPARING ONLINE POSTING TYPOLOGIES
24
Second, across both the violent and non-violent sample groups, there was a clear
incremental increase in the number of users making up each adversary posting typology, with
fewest users in the most active posting group and the greatest number of users in the least active
posting group. In addition, across four of the five adversary posting typologies (i.e., the
committed, engaged, dabbler, and non-posters) for the violent and non-violent users, their
typology patterns were generally comparable. Yet what differentiated the adversary posting
typologies of the non-violent and violent users was that, across all adversary typologies, a larger
proportion of super-posters were observed in the non-violent sample than those in the violent
sample. In other words, the non-violent sample included a larger group of users who were the
most active online in their negative discussions about Blacks, Jews, and the LGBTQ+
communities. This finding is supported by empirical research which found that non-violent
RWEs tend to be much more active online than their violent counterpart in general.
86
Research
has also found that non-violent RWEs tend to post a larger proportion of ideological posts and
those targeting their adversary groups than violent RWEs.
87
It may be the case that the non-
violent group perceive their role in and, by extension, engage with the RWE movement as
ideologues, thus providing “conceptual tools” that can be taken up by others involved in RWE
violence, which has been reported in empirical research.
88
At any rate, the results presented here
strongly suggest that the presumed positive association between posting frequency and risk of
extremist violence may not be so straightforward. This is a question of particular policy
relevance that should be investigated in future research.
Third, an assessment of the sentiment expressed by each adversary posting typology
across samples revealed that discussions about Jews tended to be the most negative, followed by
discussions about LGBTQ+s and Blacks. This finding aligns with empirical research suggesting
COMPARING ONLINE POSTING TYPOLOGIES
25
that anti-Semitic discussions are rooted in RWE ideologies
89
and in much of the RWE rhetoric
expressed online, including in RWE discussion forums
90
, social media sites,
91
and fringe
platforms.
92
However, this finding contrasts with other recent work which generally suggests that
the sentiment about LGBTQ+s in RWE forums is more negative than sentiment about Jews and
Blacks.
93
This finding also differs from some research on offline racist leaders and followers.
Ezekiel
94
, for example, in his ethnography of neo-Nazi and Klan groups in Detroit found that
leaders tended to focus on Jews as the central enemy, with African Americans, Latinos, and
Asians as merely pawns of the Jews. The followers, on the other hand, focused on Blacks as the
central enemy with little interest in Jews. Instead, followers had to be taught to hate Jews. This
finding was largely confirmed by Freilich and colleagues
95
in their macro-level assessment of
general theories of crime and politically motivated violence by the extreme right. It may then be
the case that some of the non-violent and violent users in the sample are also RWE leaders who
are teaching followers about the most serious threat to the survival of the White race (i.e., “the
Jew”, but this finding requires further exploration. Importantly, though, non-violent users in the
current study were generally more negative in each adversary typology than violent users. Again,
research suggests that the online behaviors of non-violent RWEs tend to reflect one of an
ideologue wherein they post a large proportion of messages targeting their adversary groups –
much more so than their violent counterpart
96
Nonetheless, one notably difference in sentiment
expressed by each sample group in the current study was that the violent committed posters were
generally more negative in their discussions about their adversaries than the non-violent
committed posters. As with the earlier findings regarding posting frequency, the results here
indicate that the relationship between posting sentiment and risk of violence is not simple. It is a
mistake to assume that those users posting the most negative content are necessarily users to be
COMPARING ONLINE POSTING TYPOLOGIES
26
violent. This supposition does appear to hold in some adversary contexts, and across some
typology categories, but it is not universally true. Further assessment and elaboration of the
nuanced relationship between online sentiment and offline violence is required.
Limitations and Future Research
While this study offers a first step in examining posting typologies within a sample of online
postings from violent and non-violent RWEs in one extremist community, there are several
limitations that may inform future research. Four points are worth discussing in addition to the
relatively small sample and the validity of the data being based on one key informant.
97
First, given that the validity of the data used in the current study is based on a key former
RWE informant, future research should consider the ethical issues and potential repercussions of
this type of research. To illustrate, while one informant may be unaware about some of the
violent acts of those who s/he pointed out during the identification process, asking them to
identify violent and non-violent extremists to researchers in general may lead to psychological
stress because they may experience feelings of guilt and betrayal. This, for example, may result
in strategic informing, and thus influence those included in the sample and the results of the
study in general. Further, the retrospective nature of this identification process raises questions
about the reliability of some of the former extremist’s accounts of past events, due to memory
erosion, distortion, and selective recall.
98
Conscious and unconscious retrospective bias of the
informant may also play a role in this regard, as they may have a personal revenge against past
group members, for example, which again may lead to strategic informing during the sampling
procedure.
COMPARING ONLINE POSTING TYPOLOGIES
27
Second, analyses were limited to one RWE sub-forum, and it may be case that certain
sub-forum characteristics (e.g., the topics of conversation, users and groups who post in the
space, and so on) account for some of our results. In short, researchers should examine extremist
posting typologies across various platform types, such as a comparison of violent RWE forums
with generic (non-violent) RWE forums, mainstream social media sites, fringe platforms, and
digital applications. Such comparisons would provide practitioners and policymakers with much
needed insight into the extent to which extremist posting typologies are unique to violent and
non-violent posters as well as whether such typologies span online spaces that facilitate
extremism more generally or whether certain platforms have unique functions for facilitating
extremism and associated posting compositions. This could be done in combination with a mixed
methods approach to identify key themes that emerge in the data.
Third, it is unclear if the posting typologies of the non-violent and violent RWE users in
the current study were unique to individuals who posted in the same online space generally.
Perhaps it is the case that the posting typologies of violent or non-violent RWEs are similar to
that of extremist posters in general. Future research should therefore account for the posting
typologies of the general extremist community to which the violent and non-violent extremists
participate. Lastly, unlike the growing body of literature that has identified differences in the
offline activities and behaviors of violent and non-violent extremists,
99
data for the current study
does not include information on key characteristics identified in this research such as an
individual’s employment status, criminal records, history of mental illness, extremist/radicalized
peers, and types of grievances, among many others. In short, there remain many unanswered
questions about the characteristics of those identified as violent or non-violent RWEs in the
current study. Moving ahead, research is needed to assess whether the above characteristics and
COMPARING ONLINE POSTING TYPOLOGIES
28
others mirror our sample of violent or non-violent extremists as well as whether certain
characteristics drive differential posting typologies. This could be done similar to the sampling
procedure used for the current study, wherein a former extremist would identify violent and non-
violent users, but sub-categories could be developed to capture the abovementioned key
characteristics of each identified extremist as well as to develop a scheme to further identify
differences in posting groups. This may include violent and non-violent criminal behaviors, such
as threat of violence, physical damage to property, and so on. Future research should also
identify exact moments in time that individuals engaged in offline violence and collect
information on whether their attack was planned or unplanned, the victims or targets and the
motive of the attacks, and then assess users’ posting behaviors, among other things, both before
and after the act of violence. Such an analysis may provide practitioners and policymakers with
the much-needed insight into whether specific online posting typologies escalate to physical
violence as well as assist in developing methods to identify credible threats online prior to their
engagement in violence offline.
Notes
1
Garth Davies, Ryan Scrivens, Tiana Gaudette, and Richard Frank, “A Longitudinal Comparison
of Violent and Non-Violent Right-Wing Extremist Identities Online,” in Barbara Perry, Jeff
Gruenewald, and Ryan Scrivens, Eds., Right-Wing Extremism in Canada and the United States
(Cham, Switzerland: Palgrave), in press; Ryan Scrivens, Thomas W. Wojciechowski, Joshua D.
Freilich, Steven M. Chermak, and Richard Frank, “Comparing the Online Posting Behaviors of
Violent and Non-Violent Right-Wing Extremists.” Terrorism and Political Violence. Ahead of
Print, 1-19; Ryan Scrivens, Thomas W. Wojciechowski, Joshua D. Freilich, Steven M. Chermak,
and Richard Frank, “Differentiating Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists,” Criminal Justice Policy Review. Ahead of Print, 1-23; Ryan Scrivens,
“Examining Online Indicators of Extremism among Violent and Non-Violent Right-Wing
Extremists,” Terrorism and Political Violence. Ahead of Print, 1-21.
2
See Maura Conway, “Determining the Role of the Internet in Violent Extremism and
Terrorism: Six Suggestions for Progressing Research,” Studies in Conflict & Terrorism 40, no. 1
(2017): 77-98.
3
See Ryan Scrivens, Paul Gill, and Maura Conway, “The Role of the Internet in Facilitating
Violent Extremism and Terrorism: Suggestions for Progressing Research,” in Thomas J. Holt
COMPARING ONLINE POSTING TYPOLOGIES
29
and Adam Bossler, Eds., The Palgrave Handbook of International Cybercrime and
Cyberdeviance (London, UK: Palgrave, 2020), pp. 1-22.
4
Joel Brynielsson, Andreas Horndahl, Fredik Johansson, Lisa Kaati, Christian Mårtenson, and
Pontus Svenson, “Analysis of Weak Signals for Detecting Lone Wolf Terrorists,” Security
Informatics 2, no. 11 (2013): 1-15; Katie Cohen, Fredik Johansson, Lisa Kaati, and Jonas C.
Mork, “Detecting Linguistic Markers for Radical Violence in Social Media,” Terrorism and
Political Violence 26, no. 1 (2014): 246-256; Lisa Kaati, Amendra Shrestha, and Katie Cohen,
“Linguistic Analysis of Lone Offender Manifestos,” Proceedings of the 2016 IEEE International
Conference on Cybercrime and Computer Forensics, Vancouver, BC, Canada.
5
Paul Gill and Emily Corner, “Lone-Actor Terrorist Use of the Internet and Behavioural
Correlates,” in Lee Jarvis, Stuart Macdonald, and Thomas M. Chen, Eds., Terrorism Online:
Politics, Law, Technology and Unconventional Violence (London, UK: Routledge, 2015), pp.
35-53.
6
Paul Gill, Emily Corner, Maura Conway, Amy Thornton, Mia Bloom, and John Horgan,
“Terrorist Use of the Internet by the Numbers: Quantifying Behaviors, Patterns, and Processes,”
Criminology and Public Policy 16, no. 1 (2017): 99-117.
7
Donald Holbrook and Max Taylor, “Terrorism as Process Narratives: A Study of Pre-Arrest
Media Usage and the Emergence of Pathways to Engagement,” Terrorism and Political Violence
31, no. 6 (2019): 1307-1326.
8
Tiana Gaudette, Ryan Scrivens, and Vivek Venkatesh, “The Role of the Internet in Facilitating
Violent Extremism: Insights from Former Right-Wing Extremists,” Terrorism and Political
Violence. Ahead of Print, 1-18.
9
Maura Conway, Ryan Scrivens and Logan Macnair, “Right-Wing Extremists’ Persistent Online
Presence: History and Contemporary Trends,” The International Centre for Counter-Terrorism –
The Hague 10(2019): 1-24; Thomas J. Holt, Joshua D. Freilich, and Steven M. Chermak,
“Examining the Online Expression of Ideology Among Far-Right Extremist Forum Users,”
Terrorism and Political Violence 34, no. 2 (2022): 364-384.
10
See, for example, Southern Poverty Law Center, “White Homicide Worldwide,” 1 April 2014.
Available at: https://www.splcenter.org/20140331/white-homicide-worldwide (accessed 5 March
2022).
11
See Conway et al., “Right-Wing Extremists’ Persistent Online Presence.”
12
Ben Goggin and Kalhan Rosenblatt, “Buffalo Shooting Suspect Appeared to be Active in
Online Gun Communities,” NBC News, 15 May 2022. Available at:
https://www.nbcnews.com/tech/tech-news/buffalo-shooting-peyton-gendron-live-stream-gun-
manifesto-suspect-rcna28911 (accessed 12 June, 2022).
13
Les Back, “Aryans Reading Adorno: Cyber-Culture and Twenty-First Century Racism,”
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Radical Right-Wing Posting Behaviors Online,” Deviant Behavior 41, no. 2 (2020): 216-232;
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14
Mattias Ekman, “Anti-Refugee Mobilization in Social Media: The Case of Soldiers of Odin,”
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Savvas Finkelstein, Joel Zannettou, Barry Bradlyn, and Jeremy Blackburn, “A Quantitative
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18
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22
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
23
Thomas J. Holt, Joshua D. Freilich, Steven M. Chermak, and Gary LaFree, “Examining the
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24
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25
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
26
Davies et al., “A Longitudinal Comparison of Violent and Non-Violent Right-Wing Extremist
Identities Online”
27
Scrivens et al., “Differentiating Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
28
Scrivens, “Examining Online Indicators of Extremism among Violent and Non-Violent Right-
Wing Extremists.”
29
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
30
Davies et al., “A Longitudinal Comparison of Violent and Non-Violent Right-Wing Extremist
Identities Online”; Scrivens et al., “Comparing the Online Posting Behaviors of Violent and
Non-Violent Right-Wing Extremists”; Scrivens et al., “Differentiating Online Posting Behaviors
COMPARING ONLINE POSTING TYPOLOGIES
32
of Violent and Non-Violent Right-Wing Extremists”; Scrivens, “Examining Online Indicators of
Extremism among Violent and Non-Violent Right-Wing Extremists.”
31
Bliuc et al., “Collective Identity Changes in Far-Right Online Communities”; Garth Davies,
Edith Wu, and Richard Frank, “A Witch’s Brew of Grievances: The Potential Effects of COVID-
19 on Radicalization to Violent Extremism,” Studies in Conflict & Terrorism. Ahead of Print, 1-
24; Leo Figea, Lisa Kaati, and Ryan Scrivens, “Measuring Online Affects in a White Supremacy
Forum,” Proceedings of the 2016 IEEE International Conference on Intelligence and Security
Informatics, Tucson, Arizona, USA; Philippa Levey and Martin Bouchard, “The Emergence of
Violent Narratives in the Life-Course Trajectories of Online Forum Participants,” Journal of
Qualitative Criminal Justice and Criminology 7(2019): 95-121; Logan Macnair and Richard
Frank, “Changes and Stabilities in the Language of Islamic State Magazines: A Sentiment
Analysis,” Dynamics of Asymmetric Conflict 11(2018): 109-120; Andrew J. Park, Brian Beck,
Darrick Fletche, Patrick Lam, and Herbert H. Tsang, “Temporal Analysis of Radical Dark Web
Forum Users,” Proceedings of the 2016 IEEE/ACM International Conference on Advances in
Social Networks Analysis and Mining, San Francisco, CA, USA; Matteo Vergani and Ana-Maria
Bluic, “The Evolution of the ISIS’ Language: A Quantitative Analysis of the Language of the
First Year of Dabiq Magazine,” Sicurezza, Terrorismo e Società 2(2015): 7-20; Scrivens et al.,
“Measuring the Evolution of Radical Right-Wing Posting Behaviors Online.”
32
Swati Agarwal and Ashish Sureka, “Using KNN and SVM Based One-Class Classifier for
Detecting Online Radicalization on Twitter,” Proceedings of the International Conference on
Distributed Computing and Internet Technology, Bhubaneswar, India; Adam Bermingham,
Maura Conway, Lisa McInerney, Neil O’Hare, and Alan F. Smeaton, “Combining Social
Network Analysis and Sentiment Analysis to Explore the Potential for Online Radicalisation,
Proceedings of the 2009 International Conference on Advances in Social Network Analysis
Mining, Athens, Greece; Hsinchun Chen, “Sentiment and Affect Analysis of Dark Web Forums:
Measuring Radicalization on the Internet,” Proceedings of the 2008 IEEE International
Conference on Intelligence and Security Informatics, Taipei, Taiwan; Emilio Ferrara,
“Contagion Dynamics of Extremist Propaganda in Social Networks.” Information Sciences,”
Information Sciences 418-419 (2017): 1-12; Emilio Ferrara, Wen-Qiang Wang, Onur Varol,
Alessandro Flammini, and Aram Galstyan, “Predicting Online Extremism, Content Adopters,
and Interaction Reciprocity,” Proceedings of the International Conference on Social Informatics,
Berlin, Germany; Ted Grover and Gloria Mark. “Detecting Potential Warning Behaviors of
Ideological Radicalization in an Alt-Right Subreddit,” Proceedings of the Thirteenth
International AAAI Conference on Web and Social Media, Munich, Germany, 2019; Benjamin
W. K. Hung, Anura P. Jayasumana, and Vidarshana W. Bandara. “Detecting Radicalization
Trajectories Using Graph Pattern Matching Algorithms,” Proceedings of the 2016 IEEE
International Conference on Intelligence and Security Informatics, Tucson, Arizona, USA;
Benjamin W. K. Hung, Anura P. Jayasumana, and Vidarshana W. Bandara, “Pattern Matching
Trajectories for Investigative Graph Searches,” Proceedings of the 2016 IEEE International
Conference on Data Science and Advanced Analytics, Montreal, Canada.
33
Scrivens, “Exploring Radical Right-Wing Posting Behaviors Online.”
34
Bennett Kleinberg, Isabelle van der Vegt, and Paul Gill, “The Temporal Evolution of a
Far‑Right Forum,” Journal of Computational Social Science 4 (2021): 1-23.
35
J.M. Berger and Jonathon Morgan, The ISIS Twitter Census (Washington, DC: Brookings
Institution, 2015)
COMPARING ONLINE POSTING TYPOLOGIES
33
36
Benjamin Ducol, “Uncovering the French-Speaking Jihadisphere: An Exploratory Analysis,”
Media, War and Conflict 5(2012): 51-70.
37
Stephane J. Baele, Lewys Brace, and Travis G. Coan, “From “Incel” to “Saint”: Analyzing the
Violent Worldview Behind the 2018 Toronto Attack,” Terrorism and Political Violence
33(2021): 1667-1691.
38
Amendra Shrestha, Lisa Kaati, and Katie Cohen, “A Machine Learning Approach Towards
Detecting Extreme Adopters in Digital Communities,” Proceedings of the 2017 28th
International Workshop on Database and Expert Systems Applications, Lyon, France.
39
Scrivens, “Exploring Radical Right-Wing Posting Behaviors Online.”
40
Kleinberg et al., “The Temporal Evolution of a Far‑Right Forum.”
41
Ryan Scrivens, Thomas W. Wojciechowski, and Richard Frank, “Examining the
Developmental Pathways of Online Posting Behavior in Violent Right-Wing Extremist Forums,”
Terrorism and Political Violence. Ahead of Print, 1-18.
42
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
43
Bliuc et al., “Collective Identity Changes in Far-Right Online Communities”; Pete Simi and
Robert Futrell, American Swastika: Inside the White Power Movement’s Hidden Spaces of Hate
(Second Edition) (Lanham, MD: Rowman and Littlefield Publishers, 2015).
44
Bradley Galloway and Ryan Scrivens, “The Hidden Face of Hate Groups Online: An Insider’s
Perspective,” VOX-Pol Network of Excellence Blog, January 3, 2018.
https://www.voxpol.eu/hidden-face-hate-groups-online-formers-perspective (accessed 5 March
2022).
45
See W. Chris Hale, “Extremism on the World Wide Web: A Research Review,” Criminal
Justice Studies 25, no. 4 (2010): 343-356; see also Christopher J. Lennings, Krestina L. Amon,
Heidi Brummert, and Nicholas J. Lennings, “Grooming for Terror: The Internet and Young
People,” Psychiatry, Psychology and Law 17, no. 3 (2010): 424-437; Meghan Wong, Richard
Frank, and Russell Allsup, “The Supremacy of Online White Supremacists: An Analysis of
Online Discussions of White Supremacists,” Information and Communications Technology Law
24, no. 1 (2015): 41-73.
46
See Back, “Aryans Reading Adorno”; see also Lorraine Bowman-Grieve, “Exploring
“Stormfront:” A Virtual Community of the Radical Right,” Studies in Conflict & Terrorism 32,
no. 11 (2009): 989-1007; see also Willem De Koster and Dick Houtman, “‘Stormfront is Like a
Second Home to Me:’ On Virtual Community Formation by Right-Wing Extremists,”
Information, Communication and Society 11, no. 8 (2008): 1155-1176.
47
See Futrell and Simi, “Free Spaces, Collective Identity, and the Persistence of U.S. White
Power Activism;” see also Barbara Perry and Ryan Scrivens, “White Pride Worldwide:
Constructing Global Identities Online,” in Jennifer Schweppe and Mark Walters, Eds., The
Globalisation of Hate: Internationalising Hate Crime (New York, NY: Oxford University Press,
2016), pp. 65-78.
48
See Burris et al., “White Supremacist Networks on the Internet;” see also Phyllis B.
Gerstenfeld, Diana R. Grant, and Chau-Pu Chiang, “Hate Online: A Content Analysis of
Extremist Internet Sites,” Analysis of Social Issues and Public Policy 3, no. 1 (2003): 29-44.
49
See Daniels, Cyber Racism; see also Priscilla M. Meddaugh and Jack Kay, “Hate Speech or
‘Reasonable Racism?’ The Other in Stormfront,” Journal of Mass Media Ethics 24, no. 4 (2009):
251-268.
50
Scrivens, “Exploring Radical Right-Wing Posting Behaviors Online.”
COMPARING ONLINE POSTING TYPOLOGIES
34
51
Kleinberg et al., “The Temporal Evolution of a Far‑Right Forum.”
52
Ryan Scrivens, George W. Burruss, Thomas J. Holt, Steven M. Chermak, Joshua D. Freilich,
and Richard Frank, “Triggered by Defeat or Victory? Assessing the Impact of Presidential
Election Results on Extreme Right-Wing Mobilization Online,” Deviant Behavior 42, no. 5
(2021): 630-645.
53
Scrivens et al., “Measuring the Evolution of Radical Right-Wing Posting Behaviors Online.”
54
Bliuc et al., “Collective Identity Changes in Far-Right Online Communities.”
55
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
56
Notable exceptions include Davies et al., “A Longitudinal Comparison of Violent and Non-
Violent Right-Wing Extremist Identities Online”; Scrivens, “Examining Online Indicators of
Extremism among Violent and Non-Violent Right-Wing Extremists; Scrivens et al., “Comparing
the Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists.” Scrivens et
al., “Differentiating Online Posting Behaviors of Violent and Non-Violent Right-Wing
Extremists.”
57
Davies et al., “A Longitudinal Comparison of Violent and Non-Violent Right-Wing Extremist
Identities Online”; Scrivens et al., “Comparing the Online Posting Behaviors of Violent and
Non-Violent Right-Wing Extremists”; Scrivens et al., “Differentiating Online Posting Behaviors
of Violent and Non-Violent Right-Wing Extremists”; Scrivens, “Examining Online Indicators of
Extremism among Violent and Non-Violent Right-Wing Extremists.”
58
For more information on the web-crawler, see Ryan Scrivens, Tiana Gaudette, Garth Davies,
and Richard Frank, “Searching for Extremist Content Online Using The Dark Crawler and
Sentiment Analysis,” in Mathieu Deflem and Derek M. D. Silva, Eds., Methods of Criminology
and Criminal Justice Research (Bingley, UK: Emerald Publishing, 2019), pp. 179-194.
59
September 12, 2001 was simply date that the sub-forum went live online. Based on our
assessment of the first messages posted on the sub-forum, it would appear as though Stormfront
Canada was not launched in response to the 9/11 terror attacks.
60
By former violent extremists, we refer to individuals who, at one time in their lives, subscribed
to and/or perpetuated violence in the name of a particular extremist ideology and have since
publicly and/or privately denounced violence in the name of a particular extremist ideology. In
short, they no longer identify themselves as adherents of a particular extremist ideology or are
affiliated with an extremist group or movement.
61
Data collection efforts followed the proper ethical procedures for conducting research
involving human participants. Here the former extremist was informed that their participation in
the study was entirely voluntary. They were also informed that they had the right to decline to
answer questions or to end the interview/withdraw from the study at any time. In addition, the
former was informed that they would not be identified by name in any publication, and that all
data collected from the interview would be de-identified for the purpose of ensuring participant
anonymity. One in-person interview was conducted with the former in June 2017 and was
approximately 10 hours in length. The interview was audio-recorded and transcribed.
62
This study was not an indictment of this sub-forum itself. The sub-forum was selected because
it was an online space that the former extremist actively participated in during his involvement in
violent RWE, meaning that they were familiar with the users who posted there and could identify
individuals who the former knew were violent or non-violent RWEs in the offline world.
COMPARING ONLINE POSTING TYPOLOGIES
35
63
See Davies et al., “A Longitudinal Comparison of Violent and Non-Violent Right-Wing
Extremist Identities Online”; see also Scrivens et al., “Comparing the Online Posting Behaviors
of Violent and Non-Violent Right-Wing Extremists.”
64
See J. M. Berger, Extremism (Cambridge, MA: The MIT Press, 2018).
65
See Conway et al., “Right-Wing Extremists’ Persistent Online Presence.”
66
Tore Bjørgo and Jacob Aasland Ravndal, “Extreme-Right Violence and Terrorism: Concepts,
Patterns, and Responses,” The International Centre for Counter-Terrorism – The Hague
10(2019): p. 5.
67
Josh Adams and Vincent J. Roscigno, “White Supremacists, Oppositional Culture and the
World Wide Web,” Social Forces 84, no. 2(2005): 759-778; Bowman-Grieve, “Exploring
“Stormfront;” Futrell and Simi, “Free Spaces, Collective Identity, and the Persistence of U.S.
White Power Activism.”
68
Daniels, Cyber Racism.
69
Raphael S. Ezekiel. The Racist Mind: Portraits of American Neo-Nazi and Klansmen (New
York, NY: Viking, 1995).
70
Ibid.
71
Barbara Perry. In the Name of Hate: Understanding Hate Crimes (New York, NY: Routledge,
2001).
72
For more on this procedure, see Scrivens et al., “Measuring the Evolution of Radical Right-
Wing Posting Behaviors Online.”
73
See Ronen Feldman, “Techniques and Applications for Sentiment Analysis,” Communications
of the ACM 56, no. 4 (2013): 82-89.
74
See Scrivens et al., “Searching for Extremist Content Online Using The Dark Crawler and
Sentiment Analysis.”
75
See Ryan Scrivens, Garth Davies, and Richard Frank, “Searching for Signs of Extremism on
the Web: An Introduction to Sentiment-Based Identification of Radical Authors,” Behavioral
Sciences of Terrorism and Political Aggression 10, no. 1 (2018): 39-59; see also Scrivens et al.,
“Measuring the Evolution of Radical Right-Wing Posting Behaviors Online.”
76
See Mike Thelwall and Kevan Buckley, “Topic-Based Sentiment Analysis for the Social Web:
The Role of Mood and Issue-Related Words,” Journal of the American Society for Information
Science and Technology 64, no. 8 (2013): 1608-1617.
77
For more on the functional capacity of SentiStrength, see Thelwall and Buckley, “Topic-Based
Sentiment Analysis for the Social Web.”
78
Davies et al., “A Longitudinal Comparison of Violent and Non-Violent Right-Wing Extremist
Identities Online”; Scrivens et al., “Comparing the Online Posting Behaviors of Violent and
Non-Violent Right-Wing Extremists”; Scrivens et al., “Differentiating Online Posting Behaviors
of Violent and Non-Violent Right-Wing Extremists”; Scrivens, “Examining Online Indicators of
Extremism among Violent and Non-Violent Right-Wing Extremists.”
79
Baele et al., “From “Incel” to “Saint”; Berger and Morgan, The ISIS Twitter Census; Ducol,
“Uncovering the French-Speaking Jihadisphere”; Kleinberg et al., “The Temporal Evolution of a
Far‑Right Forum”; Scrivens et al., “Examining the Developmental Pathways of Online Posting
Behavior in Violent Right-Wing Extremist Forums”; Shrestha et al., “A Machine Learning
Approach Towards Detecting Extreme Adopters in Digital Communities.”
80
Bowman-Grieve, “Exploring “Stormfront;” Wojcieszak, “‘Don’t Talk to Me.’”
81
David Huffaker, “Dimensions of Leadership and Social Influence in Online Communities,”
Human Communication Research, 36, no, 4 (2010): 593-617; Hui-Min Lai and Tsung Teng
COMPARING ONLINE POSTING TYPOLOGIES
36
Chen, “Knowledge Sharing in Interest Online Communities: A Comparison of Posters and
Lurkers,” Computers in Human Behavior 35 (2014): 295-306.
82
Thomas W. Valente and Patchareeya Pumpuang, “Identifying Opinion Leaders to Promote
Behavior Change,” Health Education & Behavior, 34, no. 6 (2007): 881-896.
83
Gaudette et al., “The Role of the Internet in Facilitating Violent Extremism.”
84
Kathleen M. Blee and Kimberly A. Creasap, “Conservative and Right-Wing Movements,”
Annual Review of Sociology 36 (2010): 269-286; Jeff Gruenewald, Joshua D. Freilich, and
Steven M. Chermak, “An Overview of the Domestic Far-Right and Its Criminal Activities,” in
Barbara Perry and Randy Blazak, Eds., Hate Crime: Issues and Perspectives, Vol. 4 Offenders
(New York, NY: Praeger, 2009), pp. 1-22; Mark S. Hamm, American Skinheads: The
Criminology and Control of Hate Crime (Westport, CT: Praeger, 1993); Barbara Perry and Ryan
Scrivens, Right-Wing Extremism in Canada (Cham, Switzerland: Palgrave, 2019); Simi and
Futrell, American Swastika.
85
Huffaker, “Dimensions of Leadership and Social Influence in Online Communities”; Gabriel
Weimann, The Influentials: People who Influence People (Albany, NY: State University of New
York Press, 1994); Youngjin Yoo and Maryam Alavi, “Emergent Leadership in Virtual Teams:
What do Emergent Leaders Do? Information and Organizatio 14, no. 1 (2004): 27-58.
86
Scrivens et al., “Comparing the Online Posting Behaviors of Violent and Non-Violent Right-
Wing Extremists.”
87
See Scrivens, “Examining Online Indicators of Extremism Among Violent and Non-Violent
Right-Wing Extremists.”
88
See, for example, Perry and Scrivens, Right-Wing Extremism in Canada.
89
Michael Barkun, “Millenarian Aspects of ‘White Supremacist’ Movements,” Terrorism and
Political Violence 1, no. 4 (1989): 409-34; Betty A. Dobratz, and Stephanie L. Shanks-Meile,
“White Power, White Pride!”: The White Separatist Movement in the United States
(Woodbridge, CT: Twayne Pub, 1997); Ezekiel, The Racist Mind; Jeffrey Kaplan, “Right Wing
Violence in North America,” Terrorism and Political Violence 7, no. 1 (1995): 44-95; Jeffrey
Kaplan, “Leaderless Resistance,” Terrorism and Political Violence 9, no. 3 (1997): 80-95.
90
Bowman-Grieve, “‘Exploring ‘Stormfront’”; Daniels, Cyber Racism; Holt et al., “Examining
the Online Expression of Ideology Among Far-Right Extremist Forum Users”; Scrivens et al.,
“Measuring the Evolution of Radical Right-Wing Posting Behaviors Online”; Scrivens,
“Exploring Radical Right-Wing Posting Behaviors Online;” Scrivens et al., “Examining Online
Indicators of Extremism in Violent Right-Wing Extremist Forums.”
91
Jacob Davey, Mackenzie Hart, and Cécile Guerin, An Online Environmental Scan of Right-
Wing Extremism in Canada: Interim Report (London, UK: Institute for Strategic Dialogue,
2020); see also Mackenzie Hart, Jacob Davey, Eisha Maharasingam-Shah, Ciaran O’Connor, and
Aoife Gallagher, An Online Environmental Scan of Right-Wing Extremism in Canada (London,
UK: Institute for Strategic Dialogue, 2021).
92
Jacob Davey and Julia Ebner, The Fringe Insurgency: Connectivity, Convergence and
Mainstreaming of the Extreme Right (London, UK: Institute for Strategic Dialogue, 2020);
Zannettou et al., “A Quantitative Approach to Understanding Online Antisemitism.”
93
Scrivens et al., “Measuring the Evolution of Radical Right-Wing Posting Behaviors Online.”
94
Ezekiel, The Racist Mind.
95
Joshua D. Freilich, Amy Adamczyk, Steven M. Chermak, Katharine A. Boyd, and William S.
Parkin, “Investigating the Applicability of Macro-Level Criminology Theory to Terrorism: A
Country-Level Analysis,Journal of Quantitative Criminology 31, no. 3 (2015): 383-411.
COMPARING ONLINE POSTING TYPOLOGIES
37
96
See Scrivens, “Examining Online Indicators of Extremism Among Violent and Non-Violent
Right-Wing Extremists.”
97
For more on these limitations, see Scrivens et al., “Comparing the Online Posting Behaviors of
Violent and Non-Violent Right-Wing Extremists.”
98
See A. D. Baddeley, “Working Memory and Reading,” Processing of Visible Language 1
(1979), pp. 355–370.
99
Horgan et al., “Actions Speak Louder Than Words”; Jasko et al., “Quest for Significance and
Violent Extremism”; Knight et al., “Comparing the Different Behavioral Outcomes of
Extremism”; LaFree et al., “Correlates of Violent Political Extremism in the United States.”
... It alleges that the so-called '(Jewish) global elites' purposefully control the influx of migrants and refugees to destroy and degrade the white or Western culture 10 . Furthermore, Scrivens (2022) reports anti-Jewish hate in their analysis, "[the Jews have used a very sinister form of eugenics for thousands of years to build an extraordinarily cunning race]" 11 . ...
... It alleges that the so-called '(Jewish) global elites' purposefully control the influx of migrants and refugees to destroy and degrade the white or Western culture 10 . Furthermore, Scrivens (2022) reports anti-Jewish hate in their analysis, "[the Jews have used a very sinister form of eugenics for thousands of years to build an extraordinarily cunning race]" 11 . ...
... Eleven narrative domains were selected after a preliminary observation of content, lasting 30 minutes per channel, was completed. To support the development of these narrative domains, a review of Schulze et al., 2021;Scrivens, 2022; and Wojciechowski et al., 2022 was conducted to include narratives and themes overlooked by the preliminary observation. Antielitism, conspiracy theory claims, racism, pro-white, antisemitic, anti-LGBT, anti-immigrant, calls for participation, anti-vaccination, anti-government, and misogynistic narratives were chosen. ...
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... While extremist forum data counts as a valuable resource in this field, its main shortcoming is that it lacks ground truth. A notable exception to this issue can be found in Scrivens et al. (2023Scrivens et al. ( , 2022, where ground truth behind an extremist forum dataset was ascertained by having a former right-wing extremist code posters on the Canadian sub-forum of Stormfront as violent or non-violent based on his experience with these members in real life. Analyses on these data have revealed different posting typologies (Scrivens et al., 2023) as well as negative attitudes of right-wing extemists towards black, jewish, and LGBTQ + communities as measured through language in the forum posts (Scrivens, Davies, Gaudette, & Frank, 2022). ...
... A notable exception to this issue can be found in Scrivens et al. (2023Scrivens et al. ( , 2022, where ground truth behind an extremist forum dataset was ascertained by having a former right-wing extremist code posters on the Canadian sub-forum of Stormfront as violent or non-violent based on his experience with these members in real life. Analyses on these data have revealed different posting typologies (Scrivens et al., 2023) as well as negative attitudes of right-wing extemists towards black, jewish, and LGBTQ + communities as measured through language in the forum posts (Scrivens, Davies, Gaudette, & Frank, 2022). Although the dataset remains small and relies on the annotation of a single individual, this endeavour can be viewed as a step in the right direction. ...
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While a growing body of evidence suggests that the Internet is a key facilitator of violent extremism, research in this area has rarely incorporated former extremists’ experiences with the Internet when they were involved in violent extremism. To address this gap, in-depth interviews were conducted with 10 Canadian former right-wing extremists who were involved in violent racist skinhead groups, with interview questions provided by 30 Canadian law enforcement officials and 10 community activists. Participants were asked about their use of the Internet and the connection between their on- and offline worlds during their involvement in the violent right-wing extremist movement. Overall, our study findings highlight the interplay between the Internet and violent extremism as well as the interactions between the on- and offline worlds of violent extremists. We conclude with a discussion of study limitations and avenues for future research.
Chapter
Right-wing extremists, among other extremists, continue to exploit the power of the Internet and associated technologies by connecting with the like-minded from around the globe and developing a sense of identity there. A growing body of literature has been dedicated to exploring this phenomenon, with an interest in how online identities of these adherents develop over time. Overlooked in these discussions, however, has been an assessment of how the development of identities of violent right-wing adherents compare to their non-violent counterpart. This study explores how 49 violent and 50 non-violent right-wing extremists frame their identities over time on a popular online space of the extreme right, Stormfront. The results highlight the extent to which the collective identities of both groups take shape over time. We conclude with a discussion of implications of this analysis and avenues for future research.
Article
Historically, pandemics had inevitably produced demonization and scapegoating, and the COVID-19 pandemic has been no exception. Some individuals and groups have attempted to weaponize and exploit the pandemic, to use it as a means of spreading their extremist ideologies and to radicalize others to their causes. Segmented regression analyses of seven online extremist forums revealed that posting behavior on violent right-wing extremist and incel forums increased significantly following the declaration of the pandemic. The same was not true of left-wing or jihadist forums. These unequal effects likely reflect the particular grievance-based and online nature of right-wing and incel extremism.
Article
Objectives Social media platforms such as Facebook are used by both radicals and the security services that keep them under surveillance. However, only a small percentage of radicals go on to become terrorists and there is a worrying lack of evidence as to what types of online behaviors may differentiate terrorists from non-violent radicals. Most of the research to date uses text-based analysis to identify "radicals" only. In this study we sought to identify new social-media level behavioral metrics upon which it is possible to differentiate terrorists from non-violent radicals. Methods: Drawing on an established theoretical framework, Social Learning Theory, this study used a matched case-control design to compare the Facebook activities and interactions of 48 Palestinian terrorists in the 100 days prior to their attack with a 2:1 control group. Conditional-likelihood logistic regression was used to identify precise estimates, and a series of binomial logistic regression models were used to identify how well the variables classified between the groups. Findings: Variables from each of the social learning domains of differential associations, definitions, differential reinforcement, and imitation were found to be significant predictors of being a terrorist compared to a nonviolent radical. Models including these factors had a relatively high classification rate, and significantly reduced error over base-rate classification. Conclusions Behavioral level metrics derived from social learning theory should be considered as metrics upon which it may be possible to differentiate between terrorists and non-violent radicals based on their social media profiles. These metrics may also serve to support textbased analysis and vice versa.