The 10 best sources that I found from my research
1. RESEARCH REPORT: Anderson, Janna, and Lee Rainie. Pew Research Center, 2023, The Future of Human Agency. https://www.pewresearch.org/internet/2023/02/24/the-future-of-human-agency/
Janna Anderson, an award-winning professor, and executive director of the Imagining the Internet Center at Elon University, collaborates with Pew Research Center in this article exploring the future of human agency in a tech-dominated era. The research involves insights from 540 technology innovators, academics, and leaders, examining the evolving relationship between humans and smart machines by 2035. The article discusses the contradiction of opinions regarding whether smart machines will enhance or diminish human control over tech-aided decision-making.
2. ARTICLE: Berkman, Robert. “Internet Searching Is Not Always What It Seems.” Chronicle of Higher Education, vol. 46, no. 47, July 2000, p. B9. EBSCOhost, https://search-ebscohost-com.skagit.idm.oclc.org/login.aspx?direct=true&db=a9h&AN=3357820&site=ehost-live.
Written by Robert Berkman, a seasoned figure in media and information with over 25 years of experience. He is the founder of The Information Advisor's Guide to Internet Research and has played various roles. He digs into the world of web rankings and how advice on improving them is shaping up. He covers basics like clear titles but warns about tricks, like blending ads with regular content. (This source is a bit old)
3. SCHOLARLY JOURNAL: Bonart, Malte, et al. "An investigation of biases in web search engine query suggestions." Online Information Review, vol. 44, no. 2, 2020, pp. 365-381. ProQuest, https://skagit.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/investigation-biases-web-search-engine-query/docview/2533110621/se-2.
The authors conducted a systematic analysis of query suggestion features in major search engines, focusing on potential biases. The research introduces a framework to assess biases in query suggestions for person-related searches on search engines like Google, Bing, and DuckDuckGo. Findings reveal semantic clusters and a slight bias in suggestions for male politicians, emphasizing the need for ongoing monitoring and auditing of web search engines to identify potential biases in query suggestions.
4. BOOK CHAPTER: Davies, Eric, et al. “SEO: The Backbone of Any Digital Marketing Strategy.” Teach Yourself: The Ultimate Marketing & PR Book, Hodder & Stoughton, London, England, 2020.https://search.credoreference.com/articles/Qm9va0FydGljbGU6NDgzNTU5Nw==?aid=102912
The origin of this source is a book called “Teach Yourself: The Ultimate Marketing & PR Book," making it a valuable, practical guide rather than an academic publication. The source how to properly handle SEO (Search Engine Optimization), emphasizing the importance of a great user experience and providing insights into Google's ranking factors.
5. RESEARCH ARTICLE: Fortunato, S., et al. "Topical Interests and the Mitigation of Search Engine Bias." Proceedings of the National Academy of Sciences, vol. 103, no. 34, 2006, pp. 12684-12689, https://doi.org/10.1073/pnas.0605525103.
Published by the Proceedings of the National Academy of Sciences (PNAS), which undergoes peer review, this article challenges the notion that search engines create a monopoly of information. The study suggests that contrary to common belief, popular sites receive less traffic than predicted, emphasizing the role of user interests and search behavior in mitigating search engine bias.
6. BOOK CHAPTER: Goldman, E. “Search engine bias and the demise of search engine utopianism.” Web Search, 2008, pp. 121–133, https://doi.org/10.1007/978-3-540-75829-7_8. Google
Eric Goldman, Associate Dean of Research and Professor of Law, specializes in Internet, IP, and advertising law. His article challenges the perception of search engine bias, arguing that it's a beneficial consequence of optimizing content for users and suggesting emerging personalized search technology will address concerns about the "winner-take-all" effect in search results.
7. ARTICLE: Holt, John D., and David J. Miller. “An evolution of search” Bulletin of the American Society for Information Science & Technology, An Evolution of Search. vol. 36, no. 1, Oct. 2009, pp. 11–15. EBSCOhost, https://doi-org.skagit.idm.oclc.org/10.1002/bult.2009.1720360105.
This article, published by ASIS&T, discusses the evolution of search technology, highlighting the shift to entity-based searching. The author explores the historical development of search systems, emphasizing improvements in precision and recall over time. This is a relatively old article.
8. BOOK: Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press, 2018, https://nyupress.org/9781479837243/algorithms-of-oppression/.
The author, Dr. Safiya U. Noble, is a renowned internet studies scholar and professor at UCLA. Recognized as a MacArthur Foundation Fellow in 2021, her work focuses on algorithmic discrimination and technology bias. Algorithms of Oppression scrutinize Google search algorithms from 2009 to 2015, exposing their racist biases. Noble argues that search algorithms perpetuate societal issues by reflecting negative biases, especially impacting women of color. The book delves into how algorithms contribute to racial and gender profiling, misrepresentation, and economic redlining.
9. BOOK CHAPTER: Werthner, Hannes, et al. “Did You Find It on the Internet? Ethical Complexities of Search Engine Rankings.” Perspectives in Digital Humanism, Springer, Cham, Switzerland, 2022, pp. 135–144, https://link.springer.com/chapter/10.1007/978-3-030-86144-5_19.
This source, written by Cansu Canca, a philosopher and AI ethics expert, delves into the ethical complexities of search engine bias. As the Founder and Director of AI Ethics Lab, Canca brings a wealth of knowledge to the argument. The chapter emphasizes the need for a rigorous public debate to address value trade-offs in developing ethical search engines, urging a comprehensive approach to navigate the complexities of search engine rankings.
10. PRO/CON ARTICLE: Search-Driven Content and Online Journalism. 7 Feb. 2011. Issues & Controversies, https://icof.infobase.com/articles/QXJ0aWNsZVRleHQ6MTYxOTk=?aid=102912.
(There does not seem to be a specific author for this source) This article, from "Issues & Controversies," explores the debate around search-driven content and content farms. The source provides a balanced view, presenting arguments from supporters who see it as a clever way to provide free content and critics who raise concerns about the impact on information quality and reliable sources. The article provides a real-world example of the seismic shift in search results during an earthquake, raising questions about the reliability and impact of content farm articles.
1. "Search engines" AND "algorithms"
2. Search engine optimization
3. "Technology evolution" AND "search engines"
4. Google's influence
5. History of search engines
6. History of information retrieval systems
7."Decision-making processes" AND "search engines"