Shaping the Web: Why the Politics of Search Engines Matters

By Lucas D. Introna, Helen Nissenbaum. The Information Society, 2000

731 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/efaa88199621af0bea3bc4cf26127731e81a82fd

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Citations in the corpus

The Debate on the Moral Responsibilities of Online Service Providers (2015, background): “…mechanisms are then suggested: embedding the value of fairness as well as [a] suite of values represented by the ideology of the Web as a public good (Introna and Nissenbaum 2006, 182) in the design of indexing and ranking algorithms, and transparency of the algorithms used by search engines.”
Bias in algorithmic filtering and personalization (2013, background): “As a result, seekers will have trouble finding the less popular and smaller sites (Nissenbaum and Introna 2000).”
In Google We Trust: Users' Decisions on Rank, Position, and Relevance (2007, background): “They compared how one page can become popular under two conditions: assuming all users do random surﬁng online versus assuming all users access information through a popularity-based for (Introna & Nissenbaum, 2000).”
Algorithmic Cultures : Essays on Meaning, Performance and New Technologies (2016, background): “Whether or not they used the term “algorithm,” investigations into the possible biases of search (Granka 2010; Halavais 2008; Introna and Nissenbaum 2000) and the personalization of news (Pariser 2012) were concerns about algorithms and their impact on culture.”
Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review (2021, background): “Another example of bias in AI concerns search engines that tend to favor certain sites over others revealing a political bias [54], and hiring algorithms tainted by “societal noise” tend to perpetuate discriminatory behaviors impacting certain individuals or groups [55].”
We get the algorithms of our ground truths: Designing referential databases in digital image processing (2017, background): “of studies: the first series of studies presents algorithms as powerful value-laden actors (Beer, 2009; Bucher, 2012; Gillespie, 2014; Hallinan and Striphas, 2016; Introna and Nissenbaum, 2000; Introna and Wood, 2004; Kraemer et al., 2011; Kushner, 2013; Steiner, 2012); the”
Governance of algorithms: options and limitations (2015, background): “Suppliers of services that rely on algorithmic selection can commit themselves to certain “values” (Introna and Nissenbaum, 2000), such as search neutrality or the “minimum principle” of data collection (Langheinrich, 2001; Cavoukia, 2009).”
Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning (2019, background): “longstanding work in computing ethics [11], [36], [37].”
Bearing Account-able Witness to the Ethical Algorithmic System (2016, background): “Design and ethics have a recent history (Buscher, Wood and Perng, 2013, Introna and Nissenbaum, 2000, and Suchman, 2011).”
"I always assumed that I wasn't really that close to [her]": Reasoning about Invisible Algorithms in News Feeds (2015, background): “For example, search algorithms structure the online information available to a society, and may function as a gatekeeper [18, 20].”
Software-sorted geographies (2005, result): “Similar software-sorting techniques have also been shown to shape the results produced by supposedly unbiased search engines in ways that favour the affiliates of the transnational media conglomerates who own search engine companies (Introna and Nissenbaum, 2000).”