- The relationship between the content that is generated by the users of social networks and their dynamics has been analyzed by many scholars. However, due to favorable data policies, the majority studies have been carried out by analyzing Twitter data. In addition, such research on Facebook (FB) groups (esp. political) is usually qualitative. The present study analyses the dynamics as well as topic dynamics of radical right political groups on FB by employing a quantitative research methodology. The current paper draws on a large data set that is comprised of posts from FB groups. Overall, there are 79 728 posts which are made up of more than 2 million words and were generated within the timespan ranging from 2010 to 2018. The experimental set up compares the general dynamics and the dynamics of activity on four topics in two radical right FB groups (i.e., pro-Russian and other radical right) in Lithuania. The results show that the year 2014 was important for the radical right FB groups in Lithuania. Newly created proRussian FB groups started growing rapidly, whereas the posting activity in other radical right FB groups started to decrease. The topic word Lithuania is relevant for the whole activity time when it comes to all the radical right FB groups. Such topic words as Russia and land correlate with national and international political crisis.
In recent years, the European Union has been witnessing the growth of radical political communities throughout Europe, including Lithuania. Many European countries are witnessing elections in which people vote for far-right and nationalist parties, even though they are at the opposite ends of a wide political spectrum. The migrant crisis accelerated a backlash against the recent political balance, but the wave of discontent also taps into long-standing fears about globalization and dilution of national identity. The increase in the percentage of radical wing voters substantially surpasses the percentage of immigration inflow [1].
The political radicals are more avid and enthusiastic to adopt new technology and have thus found the virtual space to be a uniquely useful place [2]. Through membership in groups, one can define and confirm his/her values and beliefs through incoming information or discussion. When members of such groups face uncertain situations, they can gain reassuring information about their problems and find security in companionship [3]. It is also important to highlight the fact that social media provides fertile ground for the dissemination of propaganda and disinformation as well as the manipulation of people’s perceptions and beliefs [4]. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) Social networks can become a tool for manipulating the masses and fighting wars with little to no cost.
The present paper proposes a framework for carrying out research on posts from Facebook (further FB) groups as a means to reveal information dissemination and group behavior patterns in communication by information transmission dynamics in groups. In particular, the aim of this study is to analyze the establishment of radical right FB groups in relation to the political events of the time as well as the dynamics of the most prominent themes by using the data retrieved from FB groups and R toolset. This article investigates the launch of Lithuanian radical right FB groups in a wider political context. It is important to understand the dynamics and the reasons behind the activity of such groups. Another important issue is to pinpoint when the topics discussed in the aforementioned FB groups become relevant and no longer relevant. Finding the answers to these questions can provide a deeper insight into the social processes of radical right groups on FB.
Such social networks as FB and Twitter have become the most popular social networks in the world. In 2017, Twitter had more than 330 million active users, whereas FB had more than 2.13 billion monthly active users with a 14 per cent increase every year [5]. This giant flow of information has already shown to be useful for event detection [6], identifying public health issues [7], behavioral information propagation [1], community discovery [8], sentiment analysis [9], identification of communication roles [9], and recently as a means to aid political uprising [10] as well as a medium that can help to pinpoint and analyze the act of triggering an (upcoming) uprising [11].
FB groups are the place for small group communication and for people to share their common interests and express their opinion. Such groups allow people to come together around a common cause, issue or activity in order to mobilize, express their objectives, discuss issues, post photos and share related content [12]. All FB groups have a title and a group description that indicate the common cause of group activity. FB groups can be public or closed. In the first scenario, every FB user can access group content. In the latter, content can be accessed only with a permission given by the group administrator. To comply with the ethical aspects of doing research, the present study only reports on data that has been retrieved from public FB groups.
The data were downloaded by using the FB graph API [13]. The Graph API is created to get data into and out of the FB platform. This FB platform uses low-level HTTP-based API access that can only be obtained by a user who is registered as a FB developer. For API requests, it is necessary to have the access token (app id) together with its app password and the access token.
FB API requests return the following group data [13]: post author id (from_id) as numeric string, post author name (from_name) as string, post text (message) as string, post creation date (created_time) as string, post type (type) as string, link in the post (link) as string, post id (id) as numeric string, daily entry (story) as bool, likes count (likes_count) as number, comment counts (comments) as number, shares count (shares_count) as number.
To analyze the posts of FB groups as a means of information dissemination together with the patterns of group behavior in terms of communication by information transmission dynamics in groups, the following subset of data was used: post text (message) as string, post creation date (created_time) as string, post id (id) as numeric string. To handle the large dataset more efficiently, fingerprint of each FB group was created, and it contains the names and ids as well as the names of the dataset that come from the FB groups in focus.
The radical right groups on social network FB were identified through the Facebook search engine. The supporters of radical right diverge from other individuals though manifestation of nationalism, strong nation [14] and xenophobic ideology [15]. Nationalistic ideology relates to ethnocentrism and Euroscepticism. Xenophobic ideology relates to anti-immigration policy, hostility to ethnical minorities, and intolerance to sexual minorities. To identify radical FB groups by using the FB search engine, their most prominent characteristics were taken into consideration, and based on that, the following keyword list was compiled: Lithuania, Lithuanians, land sale, European Union, NATO, refugees, refugee crisis, Muslims, Jewish restitution, Jew, Russian, Roma tabor, gay pride, gay mountaineering. More than 20 most recent posts in each group that match the keywords were analyzed. After the analysis that aimed to pinpoint the FB groups which openly exhibit radical ideology, only 10 groups that proved to endorse radical ideology were chosen for a more in-depth analysis. The FB group selection criteria were the following: the presence of radical left ideological features on group titles, description and latest posts, the size of the group (more than 100 members), activity – the most recent post published at least 2 days prior to the analysis.
The data retrieved from FB groups were divided into two datasets, pro-Russian and other radical right groups. The analysis reveals that some radical right groups in addition to the nationalistic ideology manifest pro-Russian and prosocialism ideology. Even though in some cases the titles and descriptions of the group’s manifest nationalism and the idea of strong Lithuania, there was also support for Russian politics or a sense of nostalgia for the Soviet Union. Each data set is comprised of five FB groups. As was previously indicated, to be able to handle such large amounts of data, the datasets were supplemented with additional records, i.e., the group and cluster ids. The dataset of proRussian FB groups consists of more than 70 150 posts. The second dataset, i.e. that of the other radical right groups, is comprised of 9 578 posts. The former dataset of groups has 13 940 members, whereas the latter has 6 126.
Short data info
Posts published period 4th of Ma
Lithuanian is a highly inflectional language, i.e. there are two grammatical genders for nouns and there are three genders for adjectives, numerals, participles, and pronouns. Every word must follow the gender and the number of the noun. All these features produce a substantial number of inflective forms of lemma. To avoid any loss of data, the lemmatization of the texts in FB posts was not used.
To analyze the dynamics of the topics discussed in groups, the most frequent words were employed as features [16]–[18]. In addition, social networks post timestamp modelling was applied to analyze the behavior of online users [19], [20]. This paper proposes to study the posts from FB groups as a means of information dissemination and group behavior patterns in communication by information transmission dynamics in groups. The proposed approach is based on the following observation: the amount of information passed from one period to another in the social network may be quantified in different ways. For example, in the dataset of FB groups, the amount of information can be quantified by the time that passed from one post’s appearance to other. The quantity of published group posts in a social network by looking at the time frame can show group behavior.
To grasp the information transmission when it comes to the group dynamics, the datasets of FB groups were expanded by adding fingerprints entries. Let a pro-Russian FB groups dataset be denoted by D1 and another radical right group dataset be denoted by D2. W represents time window (W = 6 months). Denote each Facebook post as eij, where i =1 represents that a post belongs to D1 and i=2 represents that post belongs to D2; = 1; where ni is the number of posts in group Di. Each post eij consists of pij, tij, gij. Each post pij, consists of a set of words pij = (wij1, wij2 … wijk), where k is the number of words in pij.
Fig. 1. Datasets of Facebook groups with expanded fingerprints entries To compare the dynamics of the users in the two datasets, the transformed dates were stored from string to POSIXct objects. To transform the dates, Lubridate [21] package for R was used. In order to visualize the distribution of groups’ activities through time, ggplot2 [22]] package for R was used. It helps to visualize the distribution of a single continuous variable by dividing the x-axis into bins and counting the number of observations in each bin. To make the text of the post tidy and the datasets lighter, Tidytext [23] and Stringr [24] packages for R were employed. By using these packages, English and Lithuanian stop words were removed. To estimate the dynamics of the topics in the collected posts, each entry (in form of sentences) was split into words. Once again, to keep track of data, every split word was supplemented with a post and dataset id, group name, and timestamp entries.
The preliminary analysis identified two types of radical
right ideology in FB groups under investigation. The
visualization in “Fig. 2” compares the dynamics of
proRussian and other radical right groups’ activity. It includes
the posts (message) of both groups’ members and post
creation time (created_time). It also shows the peak activity
periods that can be noticed in the datasets (within a time
window of six months).
The experiment shows that the activity of radical
During the course of the Ukrainian crisis, the role of
actual military interventions has remained low in comparison
to different tools of asymmetric warfare (e.g., information
warfare, economic measures, cyber war, and psychological
war on all levels), often referred to as hybrid warfare [25].
This cyber war passed national or post-Soviet Union borders
more widely and the spread of fake news reached the western
world. The conflict in the Ukraine re-awakened Russian
propaganda. For example, Twitter analyst Lawrence
Alexander has identified an increase in bot registration
coinciding with the start of the Euromaidan protests on
2013/2014 year in Ukraine and subsequent armed uprisings
by pro-Russian militants in Eastern Ukr
To analyze the dynamics of the most relevant topics in the groups, four keywords were chosen, namely, Lithuania, Russia, land, and sky. The words Lithuania, land and Russia were chosen for this experiment based on the previously defined most prominent characteristics of radical right groups. The word Russia also was chosen in order to assess and compare the dynamics of topics discussed by pro-Russian and other radical right in relation to the country. The neutral word sky was chosen to reveal whether there is any space for neutral topics in the datasets of radical right groups.
TABLE III.
Radica l right groups
ProRussian
Other Total The dynamics of the word Lithuania in the posts of radical right groups on Facebook
Year
The topic word Lithuania is relevant for all the radical right groups “Fig. 3”. This word in the posts of FB groups appears more than 22 300 times throughout the whole period of groups’ activity “table 3”. In 2014, the topics that mentioned the word Lithuania were mostly discussed by newly created pro-Russian groups rather than by other radical right groups. In 2017, both types of radical right FB groups mentioned Lithuania in the content of their posts the most frequently if compared to the previous years. Lithuania appears 5 302 times in pro-Russian groups and 857 times in radical right groups. words shows that from the beginning to the end of 2018, the words Russia appeared 16 times more than in other radical right groups. The word count indicates that the word appeared 2 864 times in pro-Russian and 178 times in other radical right groups “table 4”.
As was previously mentioned, the increased instances
of mentioning Lithuania were the most prominent in
proRussian groups. NATO Strategic Communication Centre of
Excellence claims that in the period ranging from 1
Novem
Russia-related topics seem to be more important to proRussian groups than other radical right FB groups (Fig. 4). The word analysis of the FB groups’ posts that were split to
The word Russia in the topics of pro-Russian groups
w
Creating ‘noise’ or ‘informational fog’ around a topic is a strategy used to distract attention from more strategically important events. An important example of this has been the case of the downing of Malaysian air flight MH17. Russian media channels and social media distributed a large volume of messages offering numerous explanations for why the plane crashed. Another bot campaign was launched to distract the public by offering an alternative explanation of the murder of the Russian politician Boris Nemtsov, claiming that he was killed by jealous Ukrainians. Such ‘news’ were published just a few hours after the attack [1]. The experiment shows that the word Russia in the pro-Russian groups became more actively used during the turmoil caused by Russia’s policy. This could have affected the results of the trending topics in order to make ‘noise’ or ‘informational fog’ around any given topic.
The themes related to land are more relevant to the
members of both groups. The word count estimations show
that f
The word correlates with the Lithuanian land-related
political crisis related to the restrictions imposed on
foreigners who want to purchase land for agricultural
purposes in Lithuania. The referendum by the Republic of
Lithu
In order to compare the content of the posts in radical right FB groups, a neutral keyword sky was chosen. The assessment of dynamics show that the word sky did not appear in the content produced by the radical right FB groups Radica l right 201 201 201 201 201 201 201 201 groups 0 1 2 3 4 5 6 7
ProRussian 0 0 0 0 1 5 4 13 Other 0 0 0 0 0 0 0 1 Total 0 0 0 0 1 5 4 14
This indicates that the content generated by the members of the radical right groups is similar to the political background. As Veronika Solovian, the administrator of the popular Finnish-Russian website russia.fi, admits, the trolls are commenting on political topics. They are able to attract other participants into arguments, and other users do not necessarily immediately identify them as trolls [29]. The experiment reveals that political topics are indeed relevant for radical right-wing political groups on Facebook. The largest part of the generated political content could be generated by trolls or bots. Therefore, social media provides fertile ground for the dissemination of propaganda and disinformation. The latter indicates that social media can be an effective tool to manipulate people’s mind and influence their decisions. Ease of Use
Facebook developer acc with API requests and R tools set (Lubridate, Tidytext, ggplot2) can help to analyze radical right FB groups establishment and themes dynamics. For social and political scientists, the most important result is that in Lithuania radical right groups on Facebook posts together with nationalism, strong nation and xenophobic ideology also appears topics related to the support for the Russian policy and former communist ideology. The analysis reveals that some radical right groups in addition to the nationalistic ideology manifest pro-Russian and pro-socialism ideology.
Radical right groups on Facebook sta
The topic word Lithuania is relevant for all the radical
right groups. This word in the posts of FB groups appears
more than 22 300 times throughout the whole period of
groups’ activity. The increased instances of mentioning
Lithuania were the most prominent in pro-Russian groups.
Russia-related topics seem to be more important to
proRussian groups than other radical right FB groups and
landrelated topics is more important to other radical right groups.
These topics activity correlates with national or international
political crisis: the land-related topics activity reaches its
maximum before referendum related to the restrictions
imposed on foreigners who want to purchase land for
agricultural purposes in Lithuania, the word Russia in the
topics of pro-Russian groups w
Future plans are to make different kind of radical right groups generated content most frequency words estimations and analyze it dynamics. Future work is also to analyze dynamics of FB groups incoming information and the posting dynamics of most active groups’ members.