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Abstract

The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.

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Abstract

Informational support and nurturant support are two basic types of social support offered in online health communities. This study identifies types of social support in the QuitStop forum and brings insights to exchange patterns of social support and user behaviors with content analysis and social network analysis. Motivated by user information behavior, this study defines two patterns to describe social support exchange: initiated support exchange and invited support exchange. It is found that users with a longer quitting time tend to actively give initiated support, and recent quitters with a shorter abstinent time are likely to seek and receive invited support. This study also finds that support givers of informational support quit longer ago than support givers of nurturant support, and support receivers of informational support quit more recently than support receivers of nurturant support. Usually, informational support is offered by users at late quit stages to users at early quit stages. Nurturant support is also exchanged among users within the same quit stage. These findings help us understand how health consumers are supporting each other and reveal new capabilities of online intervention programs that can be designed to offer social support in a timely and effective manner.

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Abstract

Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.

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Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik