The Influence of “Likes” on User Content Generation in Online Investment Communities

Date
2022-01-04
Authors
Zhuo, Xiaolin
Hong, Hong
Xu, Dapeng
Ye, Qiang
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
Investors increasingly rely on investment advice in online investment communities (OICs). This study analyzes the influence of the “ likes” function on the content generation in OICs. Based on the data collected from Seeking Alpha, we perform a series of analyses from the perspectives of both authors and readers. From the angle of authors, we find that authors express the logic of the articles more seriously by increasing the use of negative words, and reducing the frequency of writing articles. The reader-level analyses show that “likes” and “comments” are complementary to each other, and readers do not reduce their “comments” after the introduction of the “likes” function. In general, the launch of the new function affects the content generated by both authors and readers. Our study can enrich the research on user-generated content (UGC) and provide helpful suggestions to OIC managers in motivating users to make feedbacks and contributions in such communities.
Description
Keywords
Crowd-based Platforms, comments, likes, ugc, ugc generation, online investment communities
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 55th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.