Crowdsourcing for search engines: perspectives and challenges

Abstract

Purpose As a relatively new computing paradigm, crowdsourcing has gained enormous attention in the recent decade. Its compliance with the Web 2.0 principles, also, puts forward unprecedented opportunities to empower the related services and mechanisms by leveraging humans’ intelligence and problem solving abilities. With respect to the pivotal role of search engines in the Web and information community, this paper aims to investigate the advantages and challenges of incorporating people – as intelligent agents – into search engines’ workflow. Design/methodology/approach To emphasize the role of the human in computational processes, some specific and related areas are studied. Then, through studying the current trends in the field of crowd-powered search engines and analyzing the actual needs and requirements, the perspectives and challenges are discussed. Findings As the research on this topic is still in its infancy, it is believed that this study can be considered as a roadmap for future works in the field. In this regard, current status and development trends are delineated through providing a general overview of the literature. Moreover, several recommendations for extending the applicability and efficiency of next generation of crowd-powered search engines are presented. In fact, becoming aware of different aspects and challenges of constructing search engines of this kind can shed light on the way of developing working systems with respect to essential considerations. Originality/value The present study was aimed to portrait the big picture of crowd-powered search engines and possible challenges and issues. As one of the early works that provided a comprehensive report on different aspects of the topic, it can be regarded as a reference point.

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

“…In recent years, crowdsourcing has become increasingly prevalent in many fields and is used in a variety of tasks. When it comes to web searches, crowdsourcing is mainly related to improving underlying processes or providing users with some assistance for finding more relevant answers (Kazai, 2011; Wakamiya et al , 2011; Moradi, 2019). In addition to improve the social network site question asking experience (Jeong et al , 2013), to accurate ranking results (Kim et al , 2013; Manning et al , 2008; Doan et al , 2011), analyze logs and query submission patterns (Park et al , 2015; Zahedi et al , 2017), as a tacit approach for facilitating search process, are in the center of attention.…”

“…In this study, we therefore mainly use web search engines rather than social media. The reason for this is that modern search engine companies do not reveal the specifics of their ranking algorithms (Robertson et al , 2018; Tsuei et al , 2020; Moradi, 2019), because if they did, everybody would game the system rather than produce high-quality content. So, nobody outside the search engine companies knows specifically how rankings are calculated.…”

“…Crowdsourcing is the act of facilitating a distributed network of individuals to collaboratively solve a problem that was once performed by employees. In recent years, crowdsourcing has become increasingly prevalent in many fields and is used in a variety of tasks such as improving web search engine usage (Kazai, 2011; Wakamiya et al , 2011; Moradi, 2019). As shown by Zhitomirsky-Geffet et al (2016), aggregating judgments for a single task from several nonexpert individuals can generate results at the same level as those created by experts.…”