A collaborative trend prediction method using the crowdsourced wisdom of web search engines

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.

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