Kim K.Lee S.-Y.T.Kauffman R.J.2023-06-162023-06-162016https://hdl.handle.net/20.500.14365/3962Auburn University;Claremont Graduate University;et al.;Kennesaw State University;SAP;University Of Tennessee Chattanooga22nd Americas Conference on Information Systems: Surfing the IT Innovation Wave, AMCIS 2016 -- 11 August 2016 through 14 August 2016 -- 123256What happens when uninformed investors trade stocks via mobile phones? Do they react to social sentiment differently than more informed traders in traditional trading? Based on 16,817 data observations and econometric analysis for the trading of 251 equities in Korea over 39 days, we present evidence of herding behavior among uninformed traders in the mobile channel. The results indicate that mobile traders seem more easily swayed by changing social sentiment. In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. Mobile traders follow signals in social media suggesting that they engage in less beneficial herding behavior, based on evidence that we obtained for the occurrence of more negative feedback trading. This allows us to offer a new interpretation of how mobile channel stock trading works, and open a new portal for analytics with digital data related to the trading behavior of different investors.eninfo:eu-repo/semantics/closedAccessEconometric analysisHerding behaviorInvestor reactionsMachine learningMobile channelSocial mediaSocial sentimentStock tradingUninformed tradersValue tradersArtificial intelligenceCellular telephonesE-learningFinancial marketsInformation systemsLearning systemsMobile devicesMobile phonesSocial networking (online)Telephone setsEconometric analysisHerding behaviorsInvestor reactionsMobile channelsSocial mediaSocial sentimentStock tradingUninformed tradersValue tradersCommerceConference Object2-s2.0-84987619315