Social Search

Abstract

Social search refers to the ways in which social interaction online influences search results and social interaction is, in turn, affected. Web search is an essentially social technology inferring which information is salient in response to a given set of queries. Attempts to improve the relevance of search results draw upon the social connections of users in new ways to make inferences based on social connections and contextual information in a manner that helps to constrain the results. “Social search” emphasizes the role of social interaction and relationships in the organization of information on the World Wide Web and in other online venues. Of course, online search could not be other than social, making the term somewhat redundant, but refinements of search engine algorithms reveal the social elements in more visible ways. The most significant change in search during the early part of the twenty‐first century has been the incorporation of “social signals” in the search process, but the role of social relationships in the search process has a longer history and greater long‐term potential as compared to the role of these signs in today's algorithms.

Algorithmic probing: Prompting offensive Google results and their moderation

“…Indeed, Google's understanding evolved from the Googlearchy approach of earlier years with the introduction of personalization, which replaced universal results (Bozdag, 2013; Pariser, 2011). Personalization coupled individual users with results in their own language, locality and other preferences (derived for example from one's search history), and, significantly, advertisers also were offered those features (Halavais, 2017). The further commercialization of search also could be viewed through the prism of self-privileging (or even self-dealing), whereby search engines such as Google would return its own ‘properties’ at the top of results, driving traffic (and advertising) to itself (Jeffries and Yin, 2020).…”

Google Search and the creation of ignorance: The case of the climate crisis

“…It is not our intention to add to the already existing typologies of ignorance. Instead, we revisit Proctor's (2008) theoretical framing and tactically add to it in order to apply it to the specific conditions of a culture where sociotechnical systems configure and co-constitute not only what is to be known, but also what is not (Greyson, 2019) and where search engines and specifically Google are invisibly embedded in almost all parts of everyday life and across society (Haider and Sundin, 2019; Halavais, 2018). In his seminal text establishing the field of agnotology (ignorance studies), Proctor (2008) suggests a preliminary taxonomy to distinguish four forms of ignorance: (a) Ignorance as a resource (native state) which refers to ignorance driving curiosity and knowledge development or learning; (b) Ignorance as a selective choice (lost realm) which suggests that there are always things that we could know but do not; (c) Ignorance as an active construct or a deliberately created, strategic ploy by actors with specific intentions; (d) and Finally the notion of ignorance as a virtue, which refers to not knowing as a form of resistance or moral prudence (see also Greyson, 2019).…”

The ethical dimensions of Google autocomplete

“…Such questions rely on our individual perspectives regarding whether we think Google should facilitate the intentions of users, or aim to reinforce a particular set of values. The epistemological and ethical function of Google's results has been discussed widely in search engine studies (see Halavais, 2018: 35, Introna and Nissenbaum, 2000: 169, and Hillis et al, 2012: 182), but such discussions rarely focus on the influence of Autocomplete in determining a user's query.…”