Browsing by Author "Lee S.-Y.T."
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Conference Object Citation - Scopus: 2The Impact of Social Sentiment on Firm Performance Similarity(Association for Information Systems, 2018) Kim K.; Lee S.-Y.T.; Benyoucef M.This study aims to investigate the impact of social sentiment on firm performance similarity in financial markets. We analyze social sentiment towards a firms’ business using opinion mining techniques, and develop a social relation revealing firms’ business similarity based on the output. We found that when social trend and social sentiment about a firm vary on social media, people are likely to change their view of the firm. We found social trend to be most influential followed by negative sentiment. We use stock trade volume as an indicator of firms’ performance in two different channels (traditional and mobile), and develop social relations showing firms’ business similarity based on the output. Our findings suggest that social relations inferred from social sentiment are related to firm performance similarity. More interestingly, the relationship is stronger in the mobile channel, but it is even negative in the traditional channel.Conference Object Citation - Scopus: 7Social Sentiment and Stock Trading Via Mobile Phones(Association for Information Systems, 2016) Kim K.; Lee S.-Y.T.; Kauffman R.J.What 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.
