465 Matching Annotations
  1. Dec 2022
    1. . Furthermore, our results add to the growing body of literature documenting—at least at this historical moment—the link between extreme right-wing ideology and misinformation8,14,24 (although, of course, factors other than ideology are also associated with misinformation sharing, such as polarization25 and inattention17,37).

      Misinformation exposure and extreme right-wing ideology appear associated in this report. Others find that it is partisanship that predicts susceptibility.

    2. And finally, at the individual level, we found that estimated ideological extremity was more strongly associated with following elites who made more false or inaccurate statements among users estimated to be conservatives compared to users estimated to be liberals. These results on political asymmetries are aligned with prior work on news-based misinformation sharing

      This suggests the misinformation sharing elites may influence whether followers become more extreme. There is little incentive not to stoke outrage as it improves engagement.

    1. Exposure to elite misinformation is associated with sharing news from lower-quality outlets and with conservative estimated ideology.

      Shown is the relationship between users’ misinformation-exposure scores and (a) the quality of the news outlets they shared content from, as rated by professional fact-checkers21, (b) the quality of the news outlets they shared content from, as rated by layperson crowds21, and (c) estimated political ideology, based on the ideology of the accounts they follow10. Small dots in the background show individual observations; large dots show the average value across bins of size 0.1, with size of dots proportional to the number of observations in each bin.

    1. We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation.

    1. Therefore, although the social bot individual is “small”, it has become a “super spreader” with strategic significance. As an intelligent communication subject in the social platform, it conspired with the discourse framework in the mainstream media to form a hybrid strategy of public opinion manipulation.
    2. There were 120,118 epidemy-related tweets in this study, and 34,935 Twitter accounts were detected as bot accounts by Botometer, accounting for 29%. In all, 82,688 Twitter accounts were human, accounting for 69%; 2495 accounts had no bot score detected.In social network analysis, degree centrality is an index to judge the importance of nodes in the network. The nodes in the social network graph represent users, and the edges between nodes represent the connections between users. Based on the network structure graph, we may determine which members of a group are more influential than others. In 1979, American professor Linton C. Freeman published an article titled “Centrality in social networks conceptual clarification“, on Social Networks, formally proposing the concept of degree centrality [69]. Degree centrality denotes the number of times a central node is retweeted by other nodes (or other indicators, only retweeted are involved in this study). Specifically, the higher the degree centrality is, the more influence a node has in its network. The measure of degree centrality includes in-degree and out-degree. Betweenness centrality is an index that describes the importance of a node by the number of shortest paths through it. Nodes with high betweenness centrality are in the “structural hole” position in the network [69]. This kind of account connects the group network lacking communication and can expand the dialogue space of different people. American sociologist Ronald S. Bert put forward the theory of a “structural hole” and said that if there is no direct connection between the other actors connected by an actor in the network, then the actor occupies the “structural hole” position and can obtain social capital through “intermediary opportunities”, thus having more advantages.
    3. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.
  2. Aug 2022
  3. Apr 2022
    1. ECDC. (2021, March 8). We have cross-checked all the latest research on #FaceMasks use during the pandemic. Our position has not changed. Wear it to help slow down the spread of #COVID19! Combine it with #HandHygiene, #CoughEtiquette & #PhysicalDistancing. Be smart. Stay safe. Care about others. Https://t.co/t4AZcJVzld [Tweet]. @ECDC_EU. https://twitter.com/ECDC_EU/status/1368989564321341444

  4. Feb 2022
    1. Nursing professionals are facing with severe sleep problems during the covid 19 pandemic time. Nurses were asked to work in an environment that had a more increased level of risk than ever before. Depression and anxiety from the workplace could affect the confidence of healthcare workers in themselves as well as general trust in the healthcare system. This will lead to their turnover intention which may undermine the efforts of the governments to control the COVID-19 pandemic. The rising concern may change the working schedules of healthcare workers, offering more occupational healthcare support.

  5. Jan 2022
    1. Frenzel, S. B., Junker, N. M., Avanzi, L., Bolatov, A., Haslam, S. A., Häusser, J. A., Kark, R., Meyer, I., Mojzisch, A., Monzani, L., Reicher, S., Samekin, A., Schury, V. A., Steffens, N. K., Sultanova, L., Van Dijk, D., van Zyl, L. E., & Van Dick, R. (2022). A trouble shared is a trouble halved: The role of family identification and identification with humankind in well-being during the COVID-19 pandemic. British Journal of Social Psychology, 61(1), 55–82. https://doi.org/10.1111/bjso.12470

  6. Dec 2021
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  11. Jul 2021