Partisan search behavior and Google results in the 2018 U.S. midterm elections

ABSTRACT

This research shows that members of different ideological groups in the United States can use different search terms when looking for information about political candidates, but that difference is not enough to yield divergent search results on Google. Search engines are central in information seeking during elections, and have important implications for the distribution of information and, by extension, for democratic society. Using a method involving surveys, qualitative coding, and quantitative analysis of search terms and search results, we show that the sources of information that are returned by Google for both liberal and conservative search terms are strongly correlated. We collected search terms from people with different ideological positions about Senate candidates in the 2018 midterm election from the two main parties in the U.S., in three large and politically distinct states: California, Ohio, and Texas. We then used those search terms to scrape web results and analyze them. Our analysis shows that, in terms of the differences arising from individual search term choices, Google results exhibit a mainstreaming effect that partially neutralizes differentiation of search behaviors, by providing a set of common results, even to dissimilar searches. Based on this analysis, this article offers two main contributions: first, in the development of a method for determining group-level differences based on search input bias; and second, in demonstrating how search engines respond to diverse information seeking behavior and whether that may have implications for public discourse.

KEYWORDS:

• Search engines
• personalization
• political information
• elections
• algorithm studies

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The clustering algorithms used were the key collision fingerprint and Nearest Neighbor (Levenshtein) with a radius of 2.0 and block chars of 3.

2 Fisher's exact test is conducted in $2\times 2$ tables. In larger tables, it is possible to conduct Monte Carlo simulations of thousands of permutations of internal tables. We conducted this test with 20,000 permutations.

3 California has nonpartisan primaries, and in 2018 the two contenders for the Senate election were Democrats. However, De Lon was favored by Republicans.

Additional information

Funding

This work was supported by National Science Foundation [IIS-1717330].

Notes on contributors

Daniel Trielli

Daniel Trielli is a PhD student in the Media, Technology and Society program at the Northwestern University School of Communication. As part of the Computational Journalism Lab, he is researching how news reaches the public in our increasingly algorithmically-defined world and how journalists can cover algorithms.

Nicholas Diakopoulos

Nicholas Diakopoulos is an Assistant Professor in Communication Studies and Computer Science (by courtesy) at Northwestern University where he is Director of the Computational Journalism Lab (CJL). His research is in computational and data journalism, including aspects of automation and algorithms in news production as well as algorithmic accountability and transparency in journalism. He is the author of the book Automating the News: How Algorithms are Rewriting the Media and is co-editor of the book Data-Driven Storytelling.