{"title":"Marketing Awareness by Social Network: A Case Study of HeatTech Products","authors":"Takumi Yoshino, Arisa Takura, Y. Shirota","doi":"10.1109/ICAWST.2018.8517194","DOIUrl":null,"url":null,"abstract":"–Stock prices are likely to reflect the reputation of the company’s sales products. When the company sells a new product, if the stock price increases, we can think that the new product is welcome on the market. In the paper, we shall propose a detection model for the correlation between an SNS (Social Network Service) spike concerning the product and stock price movement. If we find an SNS spike, firstly, topic extraction is conducted on the SNS text data to remove the noise data to extract a purely breaking topic. Then, from the breaking topic distribution and period, we make the differential equation. Finally, we determine whether the solution data matches the actual stock price data. If we find the correlation between the SNS spike and the stock price change, we can predict the future stock price movement.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 9th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2018.8517194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
–Stock prices are likely to reflect the reputation of the company’s sales products. When the company sells a new product, if the stock price increases, we can think that the new product is welcome on the market. In the paper, we shall propose a detection model for the correlation between an SNS (Social Network Service) spike concerning the product and stock price movement. If we find an SNS spike, firstly, topic extraction is conducted on the SNS text data to remove the noise data to extract a purely breaking topic. Then, from the breaking topic distribution and period, we make the differential equation. Finally, we determine whether the solution data matches the actual stock price data. If we find the correlation between the SNS spike and the stock price change, we can predict the future stock price movement.
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