<abstract xmlns="http://www.w3.org/1999/xhtml">

<p><italic><bold>Background and objective</bold></italic>. Nutrition information conveyed by popular entities through online social networking sites (i.e., social media influencers) has the potential to impact consumer eating behavior through mechanisms of social influence. Little is known about how online communities of food-related social media influencers are structured, which could reveal influencers’ opportunities to observe and spread nutrition-related content and information design practices. This study explored patterns of social relationships (social capital, conservation of resources, and homophily) within a network of prominent food bloggers on Twitter (<italic>N</italic> = 44). <italic><bold>Methods</bold></italic>. Data on Twitter following/follower relationships and Twitter use (number of tweets, favorited tweets) were collected from bloggers’ Twitter profiles. Bloggers represented eight topical subcategories of food blogs (e.g., family cooking, cocktails) and comprised a one-mode social network with directed ties indicating Twitter following/follower relationships. Structural evidence of patterns of social relationships was investigated through social network visualization, centrality measures (in-degree/out-degree centrality, density, reciprocity), and inferential tests. <italic><bold>Results</bold></italic>. The overall network density of directed ties was 21%, with wide variability in individual blogger centrality across multiple measures. Cocktails, cooking, special diets, and culinary travel bloggers had more dense ties to bloggers in their own subcategories. Within the network, favorited tweets and outreach (Twitter following relationships) were positively associated with popularity (Twitter follower relationships). <italic><bold>Conclusions</bold></italic>. Food bloggers in this study formed a partially connected network, supporting the conservation of resources framework. Homophily was evident in some, but not all, topical subcategories. Associations among Twitter use, outreach, and popularity generally supported the social capital framework. Future studies should explore influencers’ motivations for connecting on social networking sites, and how content and information design practices spread among influencers.</p>
</abstract>

Exploring Patterns of Social Relationships among Food Bloggers on Twitter Using a Social Network Analysis Approach

AHEAD OF PRINT

Volume 25 (2024): Issue 1 (January 2024)

Volume 24 (2023): Issue 1 (April 2023)

Volume 23 (2022): Issue 1 (March 2022)

Volume 22 (2021): Issue 1 (September 2021)

Volume 21 (2020): Issue 1 (January 2020)

Volume 20 (2019): Issue 4 (January 2019)

Volume 20 (2019): Issue 3 (January 2019)

Volume 20 (2019): Issue 2 (January 2019)

Volume 20 (2019): Issue 1 (January 2019)

Volume 19 (2018): Issue 1 (January 2018)

Volume 18 (2017): Issue 1 (January 2017)

Volume 17 (2016): Issue 1 (January 2016)

Volume 16 (2015): Issue 1 (January 2015)

Volume 15 (2014): Issue 1 (January 2014)

Volume 14 (2013): Issue 1 (January 2013)

Volume 13 (2012): Issue 1 (January 2012)

Volume 12 (2011): Issue 1 (January 2011)

Volume 11 (2010): Issue 1 (January 2010)

Volume 10 (2009): Issue 1 (January 2009)

Journal of Social Structure

The Journal of Social Structure (JoSS) is an electronic journal of the International Network for Social Network Analysis (INSNA). It is designed to facilitate timely dissemination of state-of-the-art results in the interdisciplinary research area of the network representation of social structure. It publishes empirical, theoretical and methodological articles focused on social networks and their analysis.  JoSS is especially interested in manuscripts that are focused on social structure in network terms, that is, in terms of the patterning of social linkages among actors. These actors could be comprised of different types or levels of analysis, such as animals, humans, artificial agents, groups or organizations.  Articles are accepted only after peer review. Comments, rejoinders and extensions on already published articles will be peer-reviewed and if accepted will be attached via a hyperlink to the previously published piece.   Open Access Policy  This journal provides immediate open access to its content under the Creative Commons CC BY-NC 4.0 license on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the CC BY-NC 4.0 license users are free to share (copy and redistribute the material in any medium or format) and adapt the work (remix, transform, and build upon the material for any purpose) if the contribution was properly attributed and and used for non-commercial purposes.  ABOUT SOCIETY  International Network for Social Network Analysis is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded by Barry Wellman in 1977. INSNA was founded on the premise that the behavior and lives of social entities are affected by their position in the overall social structure. Network analysts believe that how an individual lives depends in large part on how that individual is tied into the larger web of social connections. Many believe, moreover, that the success or failure of societies and organizations often depends on the patterning of their internal structure. Social network analysis has found important applications in organizational behavior, inter-organizational relations, the spread of contagious diseases, mental health, social support, the diffusion of information and animal social organization. Today it has become an international effort with its own professional organizations, textbooks, journals, research centers, training centers and computer programs designed specifically to facilitate the analysis of social network structural data.   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 

Journal of Social Structure

Volume 20 (2019): Issue 4 (January 2019)

Exploring Patterns of Social Relationships among Food Bloggers on Twitter Using a Social Network Analysis Approach

Wyszukiwanie

Wszystkie tomy i zeszyty w tym czasopiśmie