Title :
Image Attributes and Diffusion via Twitter: The Case of #guncontrol
Author :
Stefanone, Michael A. ; Saxton, Gregory D. ; Egnoto, Michael J. ; Wei, Wayne X. ; Yun Fu
Author_Institution :
Univ. at Buffalo, Buffalo, NY, USA
Abstract :
We report on a study exploring how Twitter user attributes and the characteristics of the images they share online influence the diffusion of those images. Two-hundred and ninety unique images were collected from Twitter in October 2013 associated with the gun control hash tag [guncontrol]. A coding protocol was developed and images classified based on frame (attribute, goal, or risk), appeal (e.g. Fear, humor), and valence (positive or negative). Results indicate that shared images with attribute frames, fear and humor appeals, and positive valence are retweeted more often. Also retweeted more frequently are messages from users with larger networks and whose tweets contain hash tags. Results also show a significant negative relationship between the time since the last major shooting event in the United States and the likelihood that messages with images are retweeted. These results are discussed in the context of evolving mass media systems and online social networks.
Keywords :
social networking (online); social sciences computing; Twitter user attributes; United States; coding protocol; evolving mass media systems; guncontrol hashtag; humor appeals; image attributes; image diffusion; online social networks; positive valence; shooting event; Context; Entertainment industry; Facebook; Image coding; Media; Receivers; Twitter; Diffusion; Social Media; Social Networks;
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
DOI :
10.1109/HICSS.2015.216