Reliable hypotheses testing in animal social network analyses: global index, index of interactions and residual regression

Animal social network analyses (ASNA) have led to a foundational shift in our understanding of animal sociality that transcends the disciplinary boundaries of genetics, spatial movements, epidemiology, information transmission, evolution, species assemblages and conservation. However, some analytical protocols (i.e., permutation tests) used in ASNA have recently been called into question due to the unacceptable rates of false negatives (type I error) and false positives (type II error) they generate in statistical hypothesis testing. Here, we show that these rates are related to the way in which observation heterogeneity is accounted for in association indices. To solve this issue, we propose a method termed the "global index" (GI) that consists of computing the average of individual associations indices per unit of time. In addition, we developed an "index of interactions" (II) that allows the use of the GI approach for directed behaviours. Our simulations show that GI: 1) returns more reasonable rates of false negatives and positives, with or without observational biases in the collected data, 2) can be applied to both directed and undirected behaviours, 3) can be applied to focal sampling, scan sampling or "gambit of the group" data collection protocols, and 4) can be applied to first- and second-order social network measures. Finally, we provide a method to control for non-social biological confounding factors using linear regression residuals. By providing a reliable approach for a wide range of scenarios, we propose a novel methodology in ASNA with the aim of better understanding social interactions from a mechanistic, ecological and evolutionary perspective.

I Explain, You Collaborate, He Cheats: An Empirical Study with Social Network Analysis of Study Groups in a Computer Programming Subject

Students interact with each other in order to solve computer science programming assignments. Group work is encouraged because it has been proven to be beneficial to the learning process. However, sometimes, collaboration might be confused with dishonest behaviours. This article aimed to quantitatively discern between both cases. We collected code similarity measures from students over four academic years and analysed them using statistical and social network analyses. Three studies were carried out: an analysis of the knowledge flow to identify dishonest behaviour, an analysis of the structure of the social organisation of study groups and an assessment of the relationship between successful students and social behaviour. Continuous dishonest behaviour in students is not as alarming as many studies suggest, probably due to the strict control, automatic plagiarism detection and high penalties for unethical behaviour. The boundary between both is given by the amount of similar content and regularity along the course. Three types of study groups were identified. We also found that the best performing groups were not made up of the best individual students but of students with different levels of knowledge and stronger relationships. The best students were usually the central nodes of those groups.

Non-random Co-occurrence of Juvenile White Sharks (Carcharodon carcharias) at Seasonal Aggregation Sites in Southern California

Many terrestrial and aquatic taxa are known to form periodic aggregations, whether across life history or solely during specific life stages, that are generally governed by the availability and distribution of resources. Associations between individuals during such aggregation events are considered random and not driven by social attraction or underlying community structure. White sharks (Carcharodon carcharias) have been described as a species that exhibits resource-driven aggregative behaviors across ontogenetic stages and juvenile white sharks are known to form aggregations at specific nursery sites where individuals may remain for extended periods of time in the presence of other individuals. We hypothesized juvenile white sharks form distinct communities during these critical early phases of ontogeny and discuss how a tendency to co-occur across life stages may be seeded by the formation of these communities in early ontogeny. We present results from a series of social network analyses of 86 juvenile white sharks derived from 6 years of passive acoustic telemetry data in southern California, demonstrating the likelihood of association of tagged juvenile white sharks is greater when sharks are of similar size-classes. Individuals in observed networks exhibited behaviors that best approximated fission-fusion dynamics with spatiotemporally unstable group membership. These results provide evidence of possible non-resource driven co-occurrence and community structure in juvenile white sharks during early life stages.

Twitter Diplomacy @Kemlu_RI: A Case Study of Bali Democracy Forum 2019

Following the increasing use of social media, particularly Twitter, the Indonesian MOFA made an official Twitter account @Kemlu_RI for disseminating information. The paper aims to to analyse the trend of tweeting at the official Twitter account of the Indonesian Ministry of Foreign Affairs (MOFA), @Kemlu_RI. This research used a qualitative approach through online media, Twitter. Data was obtained through observation of the conversation trend on Twitter by monitoring @Kemlu_RI account. This research focussed on the use of hashtag #BDF2019. Using ‘Drone Emprit Academic’ (DEA), this research collected data on five days of Twitter conversation. The DEA analysis resulted in 1.088 conversations. Rather than only disseminating information, the use of DEA for analysing #BDF2019 at @Kemlu_RI turned out to produce more findings. The result of this study shows that the DEA usage gives more benefits to Indonesian digital diplomacy, such as top hashtag, top influencer, social network analyses, and most engaged users, rather than just general dissemination of information of the BDF 2019. Therefore, the use of the DEA is very significant for resulting in more accurate data for Indonesian MOFA in order to manage a better strategy for using Twitter in its future diplomatic agenda.

Political discourses, ideologies, and online coalitions in the Brazilian Congress on Twitter during 2019

The aim of this research is to describe the pattern of interactions of Brazilian legislators on Twitter during 2019 in the construction of political discourses. Based on 20,076 replies during 2019, posted on Twitter by 514 Brazilian legislators, we conducted descriptive analysis of legislators’ Twitter profiles, social network analyses from their interactions, and content analysis of the messages. We found that (1) there are large disparities between legislators in the use of Twitter; (2) the pattern of interactions depicted five clusters defined by political affinities; (3) each cluster had different features regarding their composition and impact; (4) the centrality of the legislators within the network was positively associated with public endorsement on Twitter; and (5) the topics of messages within the clusters reinforce discourses aligned to political ideologies. We argue that the pattern of interactions on Twitter allows to identify online coalitions that reinforce particular discourses within the Brazilian parliament.

Triple grief cycle of cancelled events: the emotional crisis aftermath

Purpose The coronavirus (COVID-19) pandemic response is not only devastating nations and economies across the globe but it is also severely disrupting the event industry, with government and health authorities forcing many events to be postponed or cancelled. The purpose of this study is to investigate the prospective attendees’ emotional responses to cancelled events. This study draws upon grief cycle theory to articulate different layers of the grief process in the event domain of inquiry. Design/methodology/approach The National Collegiate Athletic Association basketball tournament was selected as the research context. Taking user-generated messages from Twitter, this study first performed content analysis to organize lexical patterns into categories and higher-order themes based on the grief cycle. It also performed social network analyses using UCINET to illustrate how different grief phases are inter-related. Findings Results not only point to attendees’ self-expression manifested through a continuum of denial, anger, bargaining and acceptance but they also reveal a three-layer hierarchy of grief, namely, event-related, socio-politics-related and crisis-related. The network analysis further illustrates how grief phases are tied into a complex network of grief messages. Originality/value This study advances the event literature by improving knowledge about attendees’ emotional responses to cancelled events. It increases our understanding of the grieving process in the aftermath of COVID-19. The proposed triple grief cycle helps advance the literature by showcasing how voices from prospective attendees represent three pillars of grief hierarchy. The findings also underscore the emotional crisis of the COVID-19 aftermath.

COVID-19 Misinformation and Polarization on Twitter

This study investigated polarization on Twitter related to the COVID-19 pandemic by examining tweets containing #Plandemic (suggests the pandemic is a hoax) or #StayHome (encourages compliance with health recommendations). Over 35,000 tweets from over 25,000 users were collected in April 2020 and examined using sentiment and social network analyses. Compared to #StayHome tweets, #Plandemic tweets came from a more tightly connected network, were higher in negative emotional content, and could be sub-divided into specific categories of misinformation and conspiracy theories. To evaluate the stability of users' COVID-related perspectives, the prevalence of pro- and anti-mask sentiment was measured in same users' tweets approximately four months later. Results revealed substantial stability over time, with 40% of #Plandemic users tweeting anti-mask hashtags compared to just 2% of #StayHome users. Findings demonstrate COVID-related polarization on Twitter and have implications for public health interventions to quell the propagation of misinformation.