Online moral rhetoric and violent protests

This article is an exercise in the virtue epistemology of the internet, an area of applied virtue epistemology that investigates how online environments impact the development of intellectual virtues, and how intellectual virtues manifest within online environments. I examine online echo chambers and epistemic bubbles (Nguyen 2020, Episteme17(2), 141–61), exploring the conceptual relationship between these online environments and the virtue of open-mindedness (Battaly 2018b, Episteme15(3), 261–82). The article answers two key individual-level, virtue epistemic questions: (Q1) How does immersion in online echo chambers and epistemic bubbles affect the cultivation and preservation of open-mindedness, and (Q2) Is it always intellectually virtuous to exhibit open-mindedness in the context of online echo chambers and epistemic bubbles? In response to Q1, I contend that both online echo chambers and online epistemic bubbles threaten to undermine the cultivation and preservation of open-mindedness, albeit via different mechanisms and to different degrees. In response to Q2, I affirm that both a deficiency and excess of open-mindedness can be virtuous in these online environments, depending on the epistemic orientation of the digital user.

In this ‘age of information’, some worry that we get our news from online ‘echo chambers’, news feeds on our social media accounts that contain information from like‐minded sources. Filtering our information in this way seems prima facie problematic from an epistemic perspective. I vindicate this intuition by offering an explanation of what is wrong with online echo chambers that appeals to a particular kind of motivated reasoning, or bias due to one’s interests. This sort of bias affects, not which evidence one is exposed to, but how one makes use of the evidence that one has, on the basis of one’s interests. I argue that consulting an online echo chamber often facilitates and amplifies this bias. I then draw some general conclusions about the potential downside of having ready access to so much information.

Previous research has documented the existence of both online echo chambers and hostile intergroup interactions. In this paper, we explore the relationship between these two phenomena by studying the activity of 5.97M Reddit users and 421M comments posted over 13 years. We examine whether users who are more engaged in echo chambers are more hostile when they comment on other communities. We then create a typology of relationships between political communities based on whether their users are toxic to each other, whether echo chamber-like engagement with these communities has a polarizing effect, and on the communities' political leanings. We observe both the echo chamber and hostile intergroup interaction phenomena, but neither holds universally across communities. Contrary to popular belief, we find that polarizing and toxic speech is more dominant between communities on the same, rather than opposing, sides of the political spectrum, especially on the left; however, this mostly points to the collective targeting of political outgroups.

Introduction. Diagnostics of social identification strategies in social groups of various types has not lost its relevance for many decades. In modern conditions, the discussion and development of the methodology and methods of applied diagnostics of identification strategies in small and large social groups receives a new direction of development, thanks to the development of the theory and practice of network methods. This is due to the fact that two multidirectional processes are simultaneously developing in a network society: on the one hand, globalization, which integrates the values of people of various social entities, and, on the other hand, differentiation, dividing the society into many social groups –-social networks, striving to preserve their values and differences. Under these conditions, network diagnosis of identification strategies has several advantages.Methodology and sources. The research methodology for network diagnostics of identification strategies in social groups is formed from a combination of theoretical principles and methodological procedures that combine the advantages of a number of sociological theories: firstly, theories that consider social groups as an object of direct research; secondly, theories, which show the role and importance of identification strategies that influence the success of social identification; thirdly, theories that show the methodological principles and approaches to the formation of technologies for network diagnostics of identification strategies.Results and discussion. Network diagnostics of identification strategies is built as a set of principles and research technologies aimed at collecting and analyzing information about the goals, means and results of mastering patterns of behavior and imitation by members of social groups. Its object is the social mechanism for determining the direction and use of means of mastering standards, assigning these standards and forming behaviors that integrate and include the individual in social groups, achieving on this basis a unifyingcommon, allowing to correlate, compare and unite with groups - to achieve identity. Network diagnostics, formed on the basis of the study of values, involves the study of identification strategies as a process that can be organized in different ways. In the most general sense, these strategies are formed as conscious or unconscious standards, goals and actions leading to the result – identification. Identification strategies in a social group may differ in direction with identification strategies that are proclaimed by organizations within which, for example, small groups appear. These strategies may also differ in the goals and benchmarks of large social groups.Conclusion. There are discusses the theoretical foundations of constructing network diagnostics of identification strategies in the paper, also it contents the empirical experience of using such a technique. A modern networked society is formed as countless small groups arising on a common basis. Network identification diagnostics has several advantages of studying the standards of unity, which allows a purposeful and planned study of the success of identification in social groups.

The position an individual holds in a social network is dependent on both its direct and indirect social interactions. Because social network position is dependent on the actions and interactions of conspecifics, it is likely that the genotypic composition of individuals within a social group impacts individuals' network positions. However, we know very little about whether social network positions have a genetic basis, and even less about how the genotypic makeup of a social group impacts network positions and structure. With ample evidence indicating that network positions influence various fitness metrics, studying how direct and indirect genetic effects shape network positions is crucial for furthering our understanding of how the social environment can respond to selection and evolve. Using replicate genotypes of Drosophila melanogaster fruit flies, we created social groups that varied in their genotypic makeup. Social groups were videoed, and networks were generated using motion-tracking software. We found that both an individual's own genotype and the genotypes of conspecifics in its social group affect its position within a social network. These findings provide an early example of how indirect genetic effects and social network theory can be linked, and shed new light on how quantitative genetic variation shapes the structure of social groups. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Agricultural innovation has tremendous potentials to improve the welfare of the rural poor. Yet, many new technologies that seem profitable in demonstration plots are not widely adopted due to inadequate social groups linking the farmers to the researchers which result to non-effective information dissemination. There is no adequate link between the farmers and the social groups which are very pivotal to the adoption of innovation and its eventual usage. This study therefore looked at social network and innovation dissemination among farmers in Kwara state Nigeria. This research specifically examined the impact of social network among the farmers in the study area and estimated the correlation of individual farmer’s choices and social network behaviour. A two-stage approach was used in data selection; the first stage was purposive and second involved the random selection technique to collect data from 125 respondents in the study area. Descriptive statistic, Social Network Analysis (SNA), and Qap correlation were the tools employed. The result of the analysis showed that farmers who are members of social group adopt innovation faster. The p-value at 5% signified that there is no correlation between the farmer choice behaviour and social network behaviour. This implies that farmer tend to behave differently under different conditions as regards their choice of innovation adoption., However, when farmers are members of a social group, their decision tend to be different from when they were not and thus, there is a need for adequate information link between researchers and the farmers. Female farmers should be encouraged to join social group as measure to enhance innovation adoption. Keywords: Social Network Analysis (SNA), Qap Correlation and Innovation

Social Networks, Civil Society, Democracy and Rule of Law: A New Conceptual Framework

Twitter Geo-tags that indicate the exact location of messages have many applications from localized opinion mining during elections to efficient traffic management in critical situations. However, less than 6% of Tweets are Geo-tagged, which limits the implementation of those applications. There are two groups of solutions: content and network-based. The first group uses location indicative factors like URLs and topics, extracted from the content of tweets, to infer Geo-location for non geo-active users, whereas the second group benefits from friendship ties in the underlying social network graph. Friendship ties are better predictors compared to content information because they are less noisy and often follow the natural human spatial movement patterns. However, their prediction’s accuracy is still limited because they ignore the temporal aspects of human behavior and always assume a single location per user. This research aims to extend the current network-based approaches by taking users’ temporal dimension into account. We assume multiple locations per user during different time-slots and hypothesize that location predictability varies depending on the time and the properties of the social membership group. Thus, we propose a hierarchical solution to apply temporal categorizations on top of social network partitioning for multiple location prediction for users in Online Social Networks (OSNs) like Twitter. Given a large-scale Twitter dataset, we show that users’ location predictability exhibits different behavior in different time-slots and different social groups. We find that there are specific conditions where users are more predictable in terms of Geo-location. Our solution outperforms the state-of-the-art by improving the prediction accuracy by 16.6% in terms of Median Error Distance (MED) over the same recall.

This study specifically analyzed assessed the effect of political party online electoral mobilization on national security. Human Security and Securitization Theories explained how online electoral mobilization can threaten individual safety and national stability, and how such threats are framed to justify state security responses in Nairobi’s informal settlements. The study used a mixed-method design with 400 purposively sampled respondents from Nairobi’s informal settlements. Data were collected through interviews, questionnaires, and focus groups, and thematic analysis was applied to organize qualitative insights into themes, providing a comprehensive understanding of electoral security and social dynamics. This study observed that digital platforms can enhance electoral security by enabling real-time alerts, rumour control, and peace campaigns, helping communities and authorities prevent violence. However, they also pose risks, as misinformation, hate speech, and online echo chambers can quickly escalate tensions and undermine social cohesion, creating a national security challenge. Digital platforms aid political engagement and peace-building during elections but can also spread misinformation and incite violence, posing national security risks. Addressing this requires balanced monitoring, digital literacy, and responsible platform use.

The role social media platforms play on the emergence of polarisation is an ongoing debate in the political communication literature. Social media’s filter bubbles and online echo chambers shape people’s opinions by curating the information they have available. However, the extent to which this is the case remains unclear. Social simulation scholars have provided valuable insights into the subject through opinion dynamics models and agent-based modelling approaches. This article proposes a social simulation approach to the topic of opinion dynamics from a political communication perspective to understand how social network configurations and the media environment contribute to the emergence of national identity polarisation. We built an agent-based simulation model of national identity dynamics with a multilayer multiplex network of interacting agents in a hybrid media environment of both, traditional media and social media platforms. We use the Catalan secessionist movement to ground, contextualise and empirically inform parts of our model. We found that the initial social network setup conditions had a large impact on the emergence of polarisation amongst agents. In particular, homophily-based social networks composed of a majority of like-minded individuals produced greater polarisation compared to random networks. This was aggravated in the presence of social media filtering algorithms, selectively exposing agents to supportive information. These results emphasise the importance of both the selective exposure by social media filtering algorithms and one’s social networks (echo chambers) for polarisation to emerge. This interaction reinforces the influence of social media platforms and social networks have on the emergence of polarisation.

This article suggests that focusing on situational, interactional space provides a fruitful addition to understanding protest dynamics and the emergence of violence in protests. It suggests connecting insights from social movement research and violence research to examine what happens spatially during a protest. Examining how space can be conceptualized situationally, the article then employs document and visual data, participant observation, and interviews in a qualitative analysis and cross-case comparison of protest marches. Situational space is studied in peaceful and violent marches during three social movements (Global Justice Movement, New Social Movements, 1960s student movement). Findings suggest that a clearly defined, transparent concept of situational space during protest marches can be useful in understanding the unfolding of protest events and that situational space is of particular relevance for the emergence of protest violence. Space is not only a common comfort zone, but for protests, territory also consists of implicit power relations. Thus, spatial incursions by police officers or protesters during protests into space assigned to the other group drastically change dynamics during protest marches, lead to mistrust and rising tensions, and form a crucial bedrock for violent eruptions.

Background: Participation in peer social groups could be used in health promotion programs for the elderly. The current study investigates the effectiveness of participation in a peer social support network intervention on the self-management of the elderly with type 2 diabetes. Methods: This research is a quasi-experimental study with a pre-test-pos-ttest design with a control group conducted in 2019. Two health centers were selected as research settings from a single district in Qom Province, Iran. From each center, 46 subjects were randomly selected. Subjects in the intervention group participated in a peer social support network for 3 months (12 sessions), and the control group received only usual care. The outcome variable was self-management. The components of this variable include the level of hemoglobin A1C (HbA1C), diabetes distress (measured with Diabetes Distress Scale), awareness (measured with Davoodi’s knowledge of diabetes questionnaire), attitude (measured with diabetes attitude scale [DAS-3]), self-efficacy (measured with diabetes empowerment scale, [DES-28]), weight and blood pressure. Subjects were evaluated at baseline and at a 6-month follow-up. The obtained data were analyzed using t-test, Chi-Square, and Fisher test in SPSS software, version 22. The significance level was set at less than 0.5. Results: The change in mean HbA1C of the intervention and control groups at baseline and 6-month follow-up was -0.7 and 0.1, respectively, which was significant (P≤0.0001). Moreover, the difference in changes in the mean values of diabetes distress (P=0.008), self-efficacy (P≤0.0001), and attitude (P≤0.0001) were significant. No significant changes were found in knowledge, weight, systolic and diastolic blood pressure (P>0.05). Conclusion: The formation of social support groups may help control blood sugar in the elderly with type 2 diabetes. Seemingly, social groups can mainly impact through psychological factors such as distress control, attitude improvement, and self-efficacy enhancement.

Characterizing social networks and influence of early-life social housing in weaned heifers on pasture

A number of studies proved that social networks and social participation have beneficial health effects in western countries. However, the evidence from southeast European region is scant. We aimed to assess the extent of social networks and social participation and their relationship with self-perceived health status among older people in post-war Kosovo. A nationwide cross-sectional study was conducted in Kosovo in 2011 including a representative sample of 1890 individuals aged ≥65 years (949 men, mean age 73 ± 6 years; 941 women, mean age 74 ± 7 years; response rate: 83%). Social networks were assessed by means of number of friends and family members that participants had contacts with, whereas social participation by involvement in social groupings/organizations. Information on self-perceived health status and demographic and socioeconomic characteristics was also collected. Overall, 93% of study participants reported that they had at least weekly contacts with more than one family member, and 97% reported daily contacts with their respective friends. Conversely, only 14% of participants reported engagement with social groupings. Generally, individuals who had contacts with friends and/or engaged with social organizations reported a better health status. Our findings point to strong family ties in this patriarchal society. Conversely, levels of social participation were considerably lower in Kosovo compared with the western European countries. The low participation levels in social groupings and their putative deleterious health effects should raise the awareness of policymakers to improve the conditions and increase the degree of social participation among older people in transitional Kosovo.

The current worldwide recession has led to a reduction in spending and a tightening of budget at all levels. Measures such as cuts in wages, lower pension pay-outs and rising unemployment seem to go hand-in-hand with politically motivated violence and social instability. In recent times, certain areas of Europe have been met with widespread protests, strikes and riots such as the ones in United Kingdom (UK), Spain, and Greece. Events over the last few years in the UK have demonstrated that people are willing to go to extreme lengths for their voice to be heard. Researchers in this area are still unclear about what leads to social instability and violent protests. How can these events be predicted? What tactics can be deployed by law enforcement agencies to manage these events? Social Networks such as Twitter and Facebook have been proven to be useful tools for demonstrators to organise themselves. Instead of limiting access to these services during any future disorders, filtered information fed from these media can be used by law enforcement agencies not only to prevent using them for criminal behaviour, but also to predict these events and develop tactics to manage future protests. This papers reviews the most cited research in this area and proposes a novel theoretical framework based on digital forensics principles combined with Cloud technology, followed by a sample practical implementation for illustration.