• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.1-7
• /
• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3187-3200
• /
• 2020

Finding key users in microblog has been a research hotspot in recent years. There are two kinds of key users: obvious and hidden ones. Influence of the former is direct while that of the latter is indirect. Most of existing methods evaluate user's direct influence, so key users they can find usually obvious ones, and their ability to identify hidden key users is very low as hidden ones exert influence in a very covert way. Consequently, the algorithm of finding hidden key users based on topic transfer entropy, called TTE, is proposed. TTE algorithm believes that hidden key users are those normal users possessing a high covert influence on obvious ones. Firstly, obvious key users are discovered based on microblog propagation scale. Then, based on microblogs' topic similarity and time correlation, the transfer entropy from ordinary users' blogs to obvious key users is calculated and used to measure the covert influence. Finally, hidden influence degrees of ordinary users are comprehensively evaluated by combining above indicators with the influence of both ordinary users and obvious ones. We conducted experiments on Sina Weibo, and the results showed that TTE algorithm had a good ability to identify hidden key users.

• Information Systems Review
• /
• v.15 no.3
• /
• pp.89-110
• /
• 2013

Affiliate marketing is classified as a type of online advertising, where merchants share a percentage of sales revenue generated by each customer, who visited the company's website via a content provider. Content provider, referred to as an affiliate, usually places an online advertisement at its website. For the past few years, there have been a lot of companies or individuals who participate in affiliate marketing. Generally speaking, most of them have websites and post the merchant's ads on their own websites. However, building and maintaining websites have some technology requirements. The widespread use of Social Network Service (SNS), especially microblog-based SNS such as Twitter and Sina Weibo, provides opportunities for individuals who want to be content providers of affiliate marketing. Since information spreads quickly on microblog-based SNS and the easy in targeting customers, it is both an effective and an efficient tool to do affiliate marketing. The relationship between a content provider and the potential customer, which is referred as "tie strength", is quite an important issue in such situation. This paper proved that service characteristics of the microblog-based SNS (security, community drivenness and navigability) and content quality all had positive influence on click-through intention, while tie strength played a moderating role. For the group with strong tie, tie strength is crucial in influencing click-through intention. While for the weak tie group, content quality was very important. Finally, we proposed some implications for both academics and practitioners.