ABSTRACT
This paper proposes to utilize a search engine as a social sensor which is to be used for predicting market shares. More specifically, this paper studies a task of comparing rates of concerns of those who search for Web pages among several companies which supply products, given a specific products domain. In this paper, we measure concerns of those who search for Web pages through search engine suggests. Then, we analyze whether rates of concerns of those who search for Web pages have certain correlation with actual market share. Furthermore, as an intermediate statistics between the rates of concerns of those who search for Web pages and market share, we also examine correlations between the page view statistics at the kakaku.com site and the other two statistics. The results of the analysis show that those three statistics have certain correlations among each other.
- E. Aramaki, S. Masukawa, and M. Morita. Twitter catches the flu: Detecting influenza epidemics using Twitter. In Proc. 2011 EMNLP, pages 1568--1576, 2011. Google ScholarDigital Library
- S. Asur and B. A. Huberman. Predicting the future with social media. In Proc. WI-IAT, pages 492--499, 2010. Google ScholarDigital Library
- D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, 3:993--1022, 2003. Google ScholarDigital Library
- J. Bollen, H. Mao, and X. Zeng. Twitter mood predicts the stock market. Journal of Computational Science, 2(1):1--8, 2011.Google ScholarCross Ref
- H. S. Moat, C. Curme, A. Avakian, D. Y. Kenett, H. E. Stanley, and T. Preis. Quantifying Wikipedia usage patterns before stock market moves. Scientific Reports, 3(1801), 2013.Google Scholar
Index Terms
- Analyzing Concerns on Companies through Statistics of Search Engine Suggests and its Correlation to Market Share
Recommendations
Clustering Search Engine Suggests by Modeling Topics of Web Pages collected with Suggests
IMCOM '16: Proceedings of the 10th International Conference on Ubiquitous Information Management and CommunicationIn this paper, we address the issue of how to overview the knowledge of a given query keyword. We especially focus on concerns of those who search for Web pages with a given query keyword, and study how to efficiently overview the whole list of Web ...
A Method of Subtopic Classification of Search Engine Suggests by Integrating a Topic Model and Word Embeddings
The background of this article is the issue of how to overview the knowledge of a given query keyword. Especially, the authors focus on concerns of those who search for web pages with a given query keyword. The Web search information needs of a given ...
Overviewing the Knowledge of a Query Keyword by Clustering Viewpoints of Web Search Information Needs
WAINA '15: Proceedings of the 2015 IEEE 29th International Conference on Advanced Information Networking and Applications WorkshopsIn this paper, we address the issue of how to overview the knowledge of a given query keyword. We especially focus on concerns of those who search for Web pages with a given query keyword, and study how to efficiently overview the whole list of Web ...
Comments