TY - GEN
T1 - Sharing in social news websites
T2 - 9th International Conference on Information Technology, ITNG 2012
AU - Ma, Long
AU - Lee, Chei Sian
AU - Goh, Dion Hoe Lian
PY - 2012
Y1 - 2012
N2 - Social news websites (e.g. Digg, Reddit) have become a new and influential global phenomenon. Such websites present opportunities for individuals to participate in news creation and diffusion and thus have fundamentally transformed the ways people consume and share news. Yet, despite the popularity of these websites, factors influencing news sharing are not well documented. Hence, the objective of this study is to understand the determinants of news sharing in social news websites by examining the influence of news attributes as well as news sharers. A sample of 552 news stories was collected from a well-known and established social news website. Regression analysis was employed to analyze the data. Results indicated that in terms of news attributes, both the salience of news content and types of news were significant predictors of news sharing in social news websites. Specifically, news stories attracting more comments from users were more likely to be shared. We also found that soft news (e.g. sports and entertainment) were more frequently shared than hard news (e.g. politics and business). Contrary to expectations, the influence of news sharers did not significantly impact the extent of news sharing. The implications of the findings and directions for future research are discussed.
AB - Social news websites (e.g. Digg, Reddit) have become a new and influential global phenomenon. Such websites present opportunities for individuals to participate in news creation and diffusion and thus have fundamentally transformed the ways people consume and share news. Yet, despite the popularity of these websites, factors influencing news sharing are not well documented. Hence, the objective of this study is to understand the determinants of news sharing in social news websites by examining the influence of news attributes as well as news sharers. A sample of 552 news stories was collected from a well-known and established social news website. Regression analysis was employed to analyze the data. Results indicated that in terms of news attributes, both the salience of news content and types of news were significant predictors of news sharing in social news websites. Specifically, news stories attracting more comments from users were more likely to be shared. We also found that soft news (e.g. sports and entertainment) were more frequently shared than hard news (e.g. politics and business). Contrary to expectations, the influence of news sharers did not significantly impact the extent of news sharing. The implications of the findings and directions for future research are discussed.
KW - Information Sharing
KW - Social Media
KW - Social News Websites
KW - Social Sharing
KW - Virtual Communities
UR - http://www.scopus.com/inward/record.url?scp=84863893147&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863893147&partnerID=8YFLogxK
U2 - 10.1109/ITNG.2012.143
DO - 10.1109/ITNG.2012.143
M3 - Conference contribution
AN - SCOPUS:84863893147
SN - 9780769546544
T3 - Proceedings of the 9th International Conference on Information Technology, ITNG 2012
SP - 726
EP - 731
BT - Proceedings of the 9th International Conference on Information Technology, ITNG 2012
Y2 - 16 April 2012 through 18 April 2012
ER -