Personal Curatorial Strategy: How Do Users Select, Consume, and Manage Information on Social Media?


Student thesis: Doctoral Thesis

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Award date13 Nov 2020


Social media are increasingly used as an important source to obtain various topics of information in the current digital age. However, it is not an easy task for many users to utilize social media to retrieve information efficiently. Rapid changes in Internet technology have largely increased information availability. On a typical day, about 500 million tweets are posted on Twitter. Although there is considerably more information to deal with, our brains’ capacity to process and memorize this information is not well-suited for the task. A growing number of people are suffering from “social media fatigue,” feeling exhausted and wanting to pull back from social media because of the overwhelming informative and communicative overload. Furthermore, some users are suffering from bad experiences with highly redundant and irrelevant messages. As a result, users’ information-processing efficiency is affected because of distracted attention from irrelevant data. In addition, the heavy load of information consumption on social media could alter regular human activities’ temporal rhythms and further interrupt people’s normal daily lives.

Facing these unprecedented challenges in this age of information abundance, the work of information consumption involves not only processing information resources, but also an even heavier workload of selecting the most relevant and high-quality messages from the sea of information. Thus, the process of content curation, i.e., effectively selecting and managing online information overload in the digital media environment, has attracted increasing attention from social media scholars.

What factors could determine the sorts of information to which individuals are exposed? How do individuals cope with information-overload situations on social media? What kind of consequences could information overload bring to the information dissemination process? This dissertation proposes a theoretical framework of “personal curation,” which aims to tackle social media users’ information selection and management problems in the age of information overload. By combining both big data analytics and online experiments, this dissertation comprises three empirical studies – each focusing on one procedure in information-related processes.

The first study examines information selection mechanisms. Prior theories on information selection can be summarized into three mechanism levels: self-level interest similarity; peer influence; and global popularity. Although these three mechanism levels have been documented separately, no clear answer exists as to which level best describes selectivity decisions. Using log data from, a Chinese programming technique blog, the first study compares the strength of the three mechanisms’ effects on users’ information selection and examines the three mechanisms’ influence on further aspects of information consumption: continuous consumption after first-time exposure and consumption activity types. The findings show notable variation among the three factors’ effect strengths. Self-level interest similarity is the most dominant factor on the CSDN platform, followed by peer influence, then global popularity. Furthermore, the findings also show that only global popularity showcased consistent explanatory power for repeated consumption. In terms of blogging activity types, if the user is influenced by self-level interest similarity when reading blog content, he or she will be more likely to merely browse it, instead of participate in any feedback activities.

The second study focuses on the audience’s news feed curation in information-overload situations. Previous studies have found that people tend to experience news fatigue when they face information overload. The fatigue feelings then lead people to take information management actions. By employing an online experiment on an artificial news-browsing system, the study examines the audience’s curatorial strategy to cope with information overload and the moderated role of issue diversity on this curatorial strategy. The findings support a moderated mediation effect in which issue diversity could exacerbate the news overload effect on news feed curation via news fatigue. The experiment’s findings could help in better understanding the nature and consequences of news overload on the digital media field. Furthermore, the results also could provide theoretical implications for news curation practices in coping with the overload situation.

The third study focuses on the reposting latency of news content on social media. Reposting is an important user feedback behavior with consumed content. Response speed could reflect the user’s processing efficiency and capacity. Thus, this study regards reposting latency as a consequence of users’ information curatorial strategy and investigates the possible factors that influence users’ reposting latency. In doing so, this study employs a multilevel model to examine the effects from issue attention, temporal usage patterns, and information redundancies. The findings show that users with multi-issue attention need longer reposting time than users with single-issue attention. Furthermore, the results also show that a distributed temporal usage pattern can help shorten reposting time, whereas information redundancies and overload can increase the reposting latency of news on social media.

The dissertation’s findings contribute to our understanding of information consumption behavior on social media. The conclusions have the potential to help explain and further advise people’s personal information strategies.