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The purpose of this paper is to investigate the motivations, concerns, benefits and consequences associated with non-use of social media. In doing so, it extends Wyatt’s commonly used taxonomy of non-use by identifying new dimensions in which to understand non-use of social media. This framework encompasses a previously unidentified category of non-use that is critical to understand in today’s social media environment.

This is an exploratory interview study with 17 self-identified social media non-users distributed across age groups and socioeconomic backgrounds. A thematic analysis is conducted based on a novel extension of Wyatt’s framework and the risk-benefits framework. This is supplemented by open coding to allow for emerging themes.

This paper provides empirical insights into a formerly uninvestigated population of non-users who are prevented from using social media because of social engagement (rather than functional) barriers. It identifies how these individuals face social consequences both on and off social media, resulting in social disenfranchisement.

This is an initial exploration of the phenomenon using an interview study. For generalizability, future research should investigate non-use with a broader and random sample.

This paper includes design recommendations and implications for social media platform designers to mitigate the consequences experienced by socially disenfranchised non-users.

Addressing concerns of this newly identified class of non-users is of utmost importance. As others are increasingly connected, these non-users are left behind and even ostracized – showing the dark sides of social media use and non-use.

This work identifies types of non-use of social media previously unrecognized in the literature.

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.

This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.

After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.

The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.

Wikipedia has the lofty goal of compiling all human knowledge. The purpose of the present study is to map the structure of the Traditional Chinese Medicine (TCM) knowledge domain on Wikipedia, to identify patterns of knowledge representation on Wikipedia and to test the applicability of author bibliographic coupling analysis, an effective method for mapping knowledge domains represented in published scholarly documents, for Wikipedia data.

We adapted and followed the well-established procedures and techniques for author bibliographic coupling analysis (ABCA). Instead of bibliographic data from a citation database, we used all articles on TCM downloaded from the English version of Wikipedia as our dataset. An author bibliographic coupling network was calculated and then factor analyzed using SPSS. Factor analysis results were visualized. Factors were labeled upon manual examination of articles that authors who load primarily in each factor have significantly contributed references to. Clear factors were interpreted as topics.

Seven TCM topic areas are represented on Wikipedia, among which Acupuncture-related practices, Falun Gong and Herbal Medicine attracted the most significant contributors to TCM. Acupuncture and Qi Gong have the most connections to the TCM knowledge domain and also serve as bridges for other topics to connect to the domain. Herbal medicine is weakly linked to and non-herbal medicine is isolated from the rest of the TCM knowledge domain. It appears that specific topics are represented well on Wikipedia but their conceptual connections are not. ABCA is effective for mapping knowledge domains on Wikipedia but document-based bibliographic coupling analysis is not.

Given the prominent position of Wikipedia for both information users and for researchers on knowledge organization and information retrieval, it is important to study how well knowledge is represented and structured on Wikipedia. Such studies appear largely missing although studies from different perspectives both about Wikipedia and using Wikipedia as data are abundant. Author bibliographic coupling analysis is effective for mapping knowledge domains represented in published scholarly documents but has never been applied to mapping knowledge domains represented on Wikipedia.