Finding potential influences of a specific financial market in Twitter

This paper proposes a new framework to identify and rank Twitter accounts of which short messages or tweets may influence a specific financial stock price. In this paper, we start by mainly focusing on the first step of our framework, selecting potential influencers based on their association with a particular stock market. With numerous limitations of Twitter service to access and acquire Twitters data, a new methodology is also proposed to use a List feature to select potential financial influencers. It requires only Lists of accounts that contain an official Twitter account of the specific financial market, provided by Twitter´s users, through Twitter API. Our methodology is designed to use only a small amount of data, by which it can be practically used under the limitation of Twitter API´s crawling rate. Experimental results show that most of the potential influencers returned by our methodology are similar and related to the specific financial markets, which are companies listed on S&P 500 in this experiment. Most of the returned influencers are the official accounts of company or organization from the same sector and news media with a special emphasis on the same industry. Comparing to Twitter´s user recommendation service (Who-To-Follow) and a crowdsourcing search for topic experts (Cognos), our methodology returns more related accounts in both percentage and the number.