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Title: Sharing in social news websites: examining the influence of news attributes and news sharers
Authors: Ma, Long
Lee, Chei Sian
Goh, Dion Hoe-Lian
Issue Date: 2012
Abstract: 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.
DOI: 10.1109/ITNG.2012.143
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:WKWSCI Conference Papers

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