We present a study of the properties of network of political discussions on one of the most popular Polish Internet forums. This provides the opportunity to study the computer mediated human interactions in strongly bipolar environment. The comments of the participants are found to be mostly disagreements, with strong percentage of invective and provocative ones. Binary exchanges (quarrels) play significant role in the network growth and topology. Statistical analysis shows that the growth of the discussions depends on the degree of controversy of the subject and the intensity of personal conflict between the participants. This is in contrast to most previously studied social networks, for example networks of scientific citations, where the nature of the links is much more positive and based on similarity and collaboration rather than opposition and abuse. The work discusses also the implications of the findings for more general studies of consensus formation, where our observations of increased conflict contradict the usual assumptions that interactions between people lead to averaging of opinions and agreement.
The paper presents an analysis of the length of comments posted in Internet discussion fora, based on a collection of large datasets from several sources. We found that despite differences in the forum language, the discussed topics and user emotions, the comment length distributions are very regular and described by the lognormal form with a very high precision. We discuss possible origins of this regularity and the existence of a universal mechanism deciding the length of the user posts. We suggest that the observed lognormal dependence may be due to an entropy maximizing combination of two psychological factors which are perceived on a non-linear, logarithmic scale in accordance with the Weber-Fechner law, namely the time spent on post related considerations and the comment length itself. This hypothesis is supported by an experimental check of text length recognition capacity, confirming proportionality of the 'just noticeable differences' for text lengths -the basis of the Weber-Fechner law.
The article presents analysis of a Polish Internet political discussion forum, characterized by significant polarization and high levels of emotion. The study compares samples of discussions gathered at three periods during a 2-year time, during which events occurred that significantly increased the already strong political division of Polish society (the sudden death of the President in a plane crash, snap elections, accusations of assassination and treason). Despite these circumstances, we observe a remarkable stability of individual political support. Extensive discussions among the forum users did not lead to changes in their political affiliations or specific opinions. In contrast, emotions expressed by the forum users, mainly negative, were found to vary from post to post and between the discussion threads. An automatic emotion recognition algorithm is presented, giving results closely corresponding to human evaluations. The authors also show that differences in a user interface between the two alternative forum webpages, especially effects of features promoting direct one-to-one communication, have significant impact on message content and decrease negative emotions. Implications of such changes on promoting communication across a political divide are discussed.
Background: A realistic description of the social processes leading to the increasing reluctance to various forms of vaccination is a very challenging task. This is due to the complexity of the psychological and social mechanisms determining the positioning of individuals and groups against vaccination and associated activities. Understanding the role played by social media and the Internet in the current spread of the anti-vaccination (AV) movement is of crucial importance. Methods: We present novel, long-term Big Data analyses of Internet activity connected with the AV movement for such different societies as the US and Poland. The datasets we analyzed cover multiyear periods preceding the COVID-19 pandemic, documenting the behavior of vaccine related Internet activity with high temporal resolution. To understand the empirical observations, in particular the mechanism driving the peaks of AV activity, we propose an Agent Based Model (ABM) of the AV movement. The model includes the interplay between multiple driving factors: contacts with medical practitioners and public vaccination campaigns, interpersonal communication, and the influence of the infosphere (social networks, WEB pages, user comments, etc.). The model takes into account the difference between the rational approach of the pro-vaccination information providers and the largely emotional appeal of anti-vaccination propaganda. Results: The datasets studied show the presence of short-lived, high intensity activity peaks, much higher than the low activity background. The peaks are seemingly random in size and time separation. Such behavior strongly suggests a nonlinear nature for the social interactions driving the AV movement instead of the slow, gradual growth typical of linear processes. The ABM simulations reproduce the observed temporal behavior of the AV interest very closely. For a range of parameters, the simulations result in a relatively small fraction of people refusing vaccination, but a slight change in critical parameters (such as willingness to post anti-vaccination information) may lead to a catastrophic breakdown of vaccination support in the model society, due to nonlinear feedback effects. The model allows the effectiveness of strategies combating the anti-vaccination movement to be studied. An increase in intensity of standard pro-vaccination communications by government agencies and medical personnel is found to have little effect. On the other hand, focused campaigns using the Internet and social media and copying the highly emotional and narrative-focused format used by the anti-vaccination activists can diminish the AV influence. Similar effects result from censoring and taking down anti-vaccination communications by social media platforms. The benefit of such tactics might, however, be offset by their social cost, for example, the increased polarization and potential to exploit it for political goals, or increased ‘persecution’ and ‘martyrdom’ tropes.
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