Research Of Crowd Wisdom Based On UGC

Recent advances in information technologies have enabled the use of User-Generated Content(UGC)such as online customer reviews,which help online users interact with each other,making online community and microblog popular venues for individuals to exchange and share their opinions.Since interactions among individuals are essential for crowd wisdom,some schol arsargue that it iseasier to obtain crowd wisdom in online context.Compared to traditional media,UGC provide investors with rapidly updated information ahead of other channels,enabling peer opinions extracted online to form "crowd wisdom".In order to investigate the usefulness of online crowd wisdom and figure out factors influencing crowd performance.This study takes two popular types of UGC(i.e.,online review and online community posting)into account.The main content of this research can be divided into three parts:(1)investigating the influence of crowd wisdom extracted from UGC on product sales in and stock price prediction;(2)studying factors influencing the performance of crowd wisdom from both individual and crowd level;(3)figuring out factors influencing user continuance using intention toward mobile social media,which is the new trend of social media.This study is conducted following five main steps:(1)collecting book review data from Dangdang.com and Douban.com and building panel-data model to invesitigate the influence of internal and external online reviews on book sales;(2)proposing a new crowd opinion aggregation model,namely CrowdIQ,and applying CrowdIQ model to aggregate crowd prediction for stock price in comparison to four baseline models using real data collected from StockTwits;(3)conducting a meta-analysis to figure out factors influencing online review helpfulness;(4)using a large data set collected from a popular online investment community,i.e.,StockTwits,to investigate the impact of crowd characteristics on crowd performance;(5)conducting a survey and SEM(Structural Equation Model)with the users of a popular mobile social media,i.e.,WeChat,to investigate how to enhance users' continuance intention toward mobile social media.Crowd wisdom extracted from online reviews has influence on online consumers'decision,impacting retails'sales at the same time;crowd opinions extracted from online investment community can be used to predict stock trend.Study on online review helpfulness confirms review depth,review age,reviewer information disclosure,and reviewer expertise have positive influences on review helpfulness;helpfulness measurement,online review platform,and product type are the three factors that cause mixed findings in extant research;Moreover,study on online crowd performance postings finds that online crowd characteristics(i.e.,diversity,independence,and decentralization)are all positively related to crowd performance;furthermore,crowd size moderates the influence of crowd characteristics on crowd performance.Study on users' continuance using intention towards mobile social media finds that perceived usefulness,herd behavior and flow experience positively influence users' continuance using intention;both direct and indirect network externalities have positive impact on users' perceived usefulness.