Search

This study focuses on the changes in the global digital divide produced by language-based, algorithmic information disparities in relation to crisis-prevention resources for suicide available through the Google search engine. We used agent-based testing to emulate Google searches performed in 17 countries and in 16 different languages as a direct replication and extension of previous work. We compare data collected in 2017 with data collected in 2021. Our analyses revealed that Google searches in English from within the United States still have the highest likelihood of triggering the display of additional crisis-prevention information prominently shown in addition to the regular search results (i.e., Google's suicide-prevention result). Searches in Spanish from within the United States are informationally disadvantaged. Display rates are only slightly lower in other English-speaking countries and when searches are performed in English. While information disparities and digital divides narrowed between 2017 and 2021, substantial differences in the display of crisis-prevention resources remain observable within multilingual countries, especially when other languages compete with English. In Bahrain, South Africa, and Sweden, the crisis-prevention information functionality seems unimplemented. Our findings suggest that the use of automated computational methods is both useful to continuously observe the implementation of new algorithmic functionalities and necessary to hold global media institutions accountable for their actions. [ABSTRACT FROM AUTHOR]

Search engines are increasingly used by citizens to seek out political information. Both the high frequency of use and the high credibility attributed to them by their users emphasize the need for research on search engines' role in the democratic process. The present paper reports on a case study on online information seeking (OIS) via search engines during the 2016 US presidential election. Presidential candidate Donald Trump was largely unknown as a politician, was opposed by the vast majority in elite circles, broke the standard niceties of politics, and practiced a style of politics based on riot and conflict. Based on these attention-gaining maneuvers, we predicted that citizens would show an OIS bias toward Trump (compared to Hillary Clinton). Importantly, we hypothesized that key events broadly categorizable as gaffes, scandal, or gossip influenced OIS bias due to a general negativity bias. We used a retrospective database study relying on query share data from the search engine Google to test these assumptions. Consistent with our predictions, we found that there was a substantial OIS bias toward Trump and that negatively-valenced key events influenced the size of the OIS bias meaningfully. Of interest, additional analyses revealed a correlation between OIS bias and election outcome: The higher the OIS bias toward Trump, the less citizens voted for Trump. We offer post hoc theorizing on this explorative finding. [ABSTRACT FROM AUTHOR]