Dynamics of hate based Internet user networks

Sobkowicz, Paweł; Sobkowicz, Antoni

doi:10.1140/epjb/e2010-00039-0

Cited by 69 publications

(67 citation statements)

References 36 publications

(28 reference statements)

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“…. The analysis of the political discussion fora confirms this reasoning [38,52,53]. Even in the situations where proponents of the opposing opinions actively seek out contact with each other, the chances of influencing the opinion of the opponents are practically zero.…”

Section: Discussionmentioning

confidence: 61%

Extremism without extremists: Deffuant model with emotions

Sobkowicz

2015

Front. Phys.

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The frequent occurrence of extremist views in many social contexts, often growing from small minorities to almost total majority, poses a significant challenge for democratic societies. The phenomenon can be described within the sociophysical paradigm. We present a modified version of the continuous bounded confidence opinion model, including a simple description of the influence of emotions on tolerances, and eventually on the evolution of opinions. Allowing for psychologically based correlation between the extreme opinions, high emotions and low tolerance for other people's views leads to quick dominance of the extreme views within the studied model, without introducing a special class of agents, as has been done in previous works. This dominance occurs even if the initial numbers of people with extreme opinions is very small. Possible suggestions related to mitigation of the process are briefly discussed.

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Section: Discussionmentioning

confidence: 61%

Extremism without extremists: Deffuant model with emotions

Sobkowicz

2015

Front. Phys.

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“…Various aspects of the subject have been of broad interest recently [3][4][5]. Some of the regularities presented here are now known among researchers (in particular the relationship describing the number of entries to the mailing lists, or comments posted on blogs) on the rank of list member (its order in the list of the users that are most frequently writing there).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Users Activity on Web-Blogs

Kozioł

2016

Acta Phys. Pol. A

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Activity of users on Internet discussion forums is analyzed. The rank of users is shown to be approximated better by stretched-exponential function than by the Zipf law. Cumulative distribution function is found as an excellent tool in analysis of the dynamics of the collective social phenomena. We are able to approximate the number of blog comments with time by simple sigmoidal functions: probability of posting a comment is given by P (t) = P0(t)/[1 + P0(t)], where P0(t) = (t/t0) β and β is close to 1.

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“…In Ref. 24, the authors studied political discussions on an Internet forum. They chose several hundred posts and identified their sentiments.…”

Section: Introductionmentioning

confidence: 99%

“…25. These studies 24,25 raise the question of whether traditional opinion models suitably describe online opinion interactions, and whether the interacting rules reflect the actual characteristics of human behavior. Except for these few studies, due to the limitations of data acquisition and processing capability, large-scale empirical analysis has seldom been carried out to check the validity of opinion models.…”

Section: Introductionmentioning

confidence: 99%

Opinion formation on social media: An empirical approach

Xiong

Liu

2014

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Opinion exchange models aim to describe the process of public opinion formation, seeking to uncover the intrinsic mechanism in social systems; however, the model results are seldom empirically justified using large-scale actual data. Online social media provide an abundance of data on opinion interaction, but the question of whether opinion models are suitable for characterizing opinion formation on social media still requires exploration. We collect a large amount of user interaction information from an actual social network, i.e., Twitter, and analyze the dynamic sentiments of users about different topics to investigate realistic opinion evolution. We find two nontrivial results from these data. First, public opinion often evolves to an ordered state in which one opinion predominates, but not to complete consensus. Second, agents are reluctant to change their opinions, and the distribution of the number of individual opinion changes follows a power law. Then, we suggest a model in which agents take external actions to express their internal opinions according to their activity. Conversely, individual actions can influence the activity and opinions of neighbors. The probability that an agent changes its opinion depends nonlinearly on the fraction of opponents who have taken an action. Simulation results show user action patterns and the evolution of public opinion in the model coincide with the empirical data. For different nonlinear parameters, the system may approach different regimes. A large decay in individual activity slows down the dynamics, but causes more ordering in the system. Opinion dynamics tries to describe the process of public opinion formation in social systems. Many opinion models have been presented that explore how the local individual behavior affects collective phenomena. However, those model results are seldom empirically justified using large-scale actual data, and whether traditional opinion models suitably describe online opinion interactions requires further exploration. We analyze users' opinions regarding a certain topic using large-scale actual data collected from a famous social network, i.e., Twitter, and discover two nontrivial results: first, consensus is difficult to achieve in a finite time and second, users seldom change their opinions, and the number of individual opinion changes decays as a power law. We present a discrete opinion model including agents' internal opinions and external actions that are determined by agents' activity. Agents' activity also evolves during the dynamics. Simulation results show our model can retrieve similar properties to those of actual data. We hope theoretical opinion models will be verified by actual data in different social systems so that they can better characterize actual social interactions. In the future, whether opinion models can predict the evolutionary trend of public opinion in actual situation will be investigated. This study will improve the applicability of research on opinion dynamics.

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Dynamics of hate based Internet user networks

Cited by 69 publications

References 36 publications

Extremism without extremists: Deffuant model with emotions

Extremism without extremists: Deffuant model with emotions

Dynamics of Users Activity on Web-Blogs

Opinion formation on social media: An empirical approach

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