A collaborative trend prediction method using the crowdsourced wisdom of web search engines
Data Technologies and Applications
ISSN: 2514-9288
Article publication date: 28 March 2022
Issue publication date: 9 December 2022
Abstract
Purpose
The purpose of this paper is to propose a novel collaborative trend prediction method to estimate the status of trending topics by crowdsourcing the wisdom in web search engines. Government officials and decision makers can take advantage of the proposed method to effectively analyze various trending topics and make appropriate decisions in response to fast-changing national and international situations or popular opinions.
Design/methodology/approach
In this study, a crowdsourced-wisdom-based feature selection method was designed to select representative indicators showing trending topics and concerns of the general public. The authors also designed a novel prediction method to estimate the trending topic statuses by crowdsourcing public opinion in web search engines.
Findings
The authors’ proposed method achieved better results than traditional trend prediction methods and successfully predict trending topic statuses by using the crowdsourced wisdom of web search engines.
Originality/value
This paper proposes a novel collaborative trend prediction method and applied it to various trending topics. The experimental results show that the authors’ method can successfully estimate the trending topic statuses and outperform other baseline methods. To the best of the authors’ knowledge, this is the first such attempt to predict trending topic statuses by using the crowdsourced wisdom of web search engines.
Keywords
Acknowledgements
This research was supported in part by MOST 109-2410-H-002 -071 -MY2 from the Ministry of Science and Technology, Republic of China.
Citation
Fang, Z.-H. and Chen, C.C. (2022), "A collaborative trend prediction method using the crowdsourced wisdom of web search engines", Data Technologies and Applications, Vol. 56 No. 5, pp. 741-761. https://doi.org/10.1108/DTA-08-2021-0209
Publisher
:Emerald Publishing Limited
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