When Do "Likes" Create Bias?

被引:0
|
作者
Hao, Hui [1 ]
Hess, Traci [1 ]
机构
[1] Univ Massachusetts Amherst, Amherst, MA 01003 USA
来源
关键词
Cognitive bias; elaboration likelihood model; number of "likes; topic relevance; question answering sites; ONLINE PRODUCT REVIEWS; COMMUNITIES; MODEL; USER; SYSTEMS; RATINGS; ANSWER;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The rise of online communities has ushered in a new era of content sharing with platforms that serve many functions and overcome the geographic and synchronous limitations of traditional word-of-mouth communications. Community-based question answering sites (CQA) have emerged as convenient platforms for users to exchange knowledge and opinions with others. Research on CQA has primarily focused on engaging members to voluntarily contribute to these communities. Helpfulness ratings and "likes" are one mechanism platforms can use to engage members, but these subjective evaluations can also create bias. In this ERF paper, the elaboration likelihood model is applied to better understand when bias can occur with these platforms. An experimental design and a planned data collection are reported.
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页数:5
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