Google chemtrails: A methodology to analyze topic representation in search engine results

Andrea Ballatore

doi:10.5210/fm.v20i7.5597

Abstract

Search engine results influence the visibility of different viewpoints in political, cultural, and scientific debates. Treating search engines as editorial products with intrinsic biases can help understand the structure of information flows in new media. This paper outlines an empirical methodology to analyze the representation of topics in search engines, reducing the spatial and temporal biases in the results. As a case study, the methodology is applied to 15 popular conspiracy theories, examining type of content and ideological bias, demonstrating how this approach can inform debates in this field, specifically in relation to the representation of non-mainstream positions, the suppression of controversies and relativism.

Highlights

This paper contributes to this area of research by designing a methodology to collect and analyze such search engine results, reducing the geographic and temporal biases in the data to extract stable, representative Web content
More academic sources are returned in the case of vaccinerelated conspiracies (19.8 percent), and of Holocaust revisionism (16.8 percent)
This paper presented a methodology to study the representation of topics in popular search engines, extracting stable, highly visible results from a large number of volatile search results

Summary

Introduction

As Hillis, et al (2013) pointed out, search technologies exert powerful socioeconomic and political influence on society Considering their ubiquity, Grimmelmann (2010) states that “search engines are the new mass media ... This paper contributes to this area of research by designing a methodology to collect and analyze such search engine results, reducing the geographic and temporal biases in the data to extract stable, representative Web content. Such stable content can be treated as editorial content and analyzed along multiple dimensions. The methodology is deployed to study the representation of these 15 topics, answering the following questions:

Methods

Results

Conclusion