Análisis de respuestas enriquecidas en Google

  1. Sonia Sánchez Cuadrado 1
  2. Jorge Morato 2
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

  2. 2 Universidad Carlos III de Madrid
    info

    Universidad Carlos III de Madrid

    Madrid, España

    ROR https://ror.org/03ths8210

Revista:
Scire: Representación y organización del conocimiento

ISSN: 1135-3716

Ano de publicación: 2023

Volume: 29

Número: 1

Páxinas: 13-23

Tipo: Artigo

DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Scire: Representación y organización del conocimiento

Resumo

In Web Information Retrieval, search engines, such as Google, includefeatures that return direct responses to user queries. These answers try to solve an infor-mation need and are known as rich answers. To find out how these results are presented and how it affects search engine optimization, an analysis of the featured direct responses presented by Google has been car-ried out. In this work, a collection of informational ques-tions expressed in natural language with the terms "what is" has been examined. The ranking of results has been analysed, identified the characteristics of the direct responses.Also, SEO factors that can determine the relevance of the fragment with respect to the query have been explored. This work confirms that the an-swer is not necessarily taken literally from the web pageand confirms that the solution to the questions can come from various resources. The direct response fragments and other rich answers can occupy close to half of the main results page, taking on a greater role and scroll down the rest of the organic results. Direct answers provide a change in search habits and a new way of browsing the web based on a hyperlinked ques-tion-answer system

Referencias bibliográficas

  • Bernstein, Michael S.; Teevan, Jaime; Dumais, Susan; Lie-bling, Daniel; Horvitz, Eric (2012). Direct answers for search queries in the long tail. // Proceedings of the SIG-CHI Conference on Human Factors in Computing Systems. Austin Texas USA: ACM 237-246. ISBN 9781450310154. https://doi.org/10.1145/2207676.2207710
  • Bilal, Dania; Huang, Li-Min (2019). Readability and word complexity of SERPs snippets and web pages on children’s search queries: Google vs Bing. // Aslib Journal of Information Management.71:2,241–259. https://doi.org/10.1108/AJIM-05-2018-0124
  • Bink, Markus; Zimmerman, Steven; Elsweiler, David (2022). Featured Snippets and their Influence on Users’ Credibility Judgements. // ACM SIGIR Conference on Human Information Interaction and Retrieval, 113–122. https://doi.org/10.1145/3498366.3505766
  • Brita-Paja Nuñez, P. (2022). Elementos de posicionamiento de los sistemas de pregunta respuesta de la web. Getafe: Universidad Carlos III de Madrid. Trabajo Fin de Grado. http://hdl.handle.net/10016/36335
  • Broder, Andrei (2002). A taxonomy of web search. // ACM SI-GIR Forum, 36:2, 3–10. https://doi.org/10.1145/792550.792552
  • Chen, Wei-Fan; Hagen, Matthias; Stein, Benno; Potthast, Martin (2018) A User Study on Snippet Generation: Text Reuse vs. Paraphrases. // The 41st International ACM SI-GIR Conference on Research & Development in Information Retrieval.1033–1036. https://doi.org/10.1145/3209978.3210149
  • Duong, Véronique (2019). State of the Art of SEO.// SEO Management: Methods and Techniques to Achieve Success(1.a ed., pp. 1-9). Wiley Data and Cybersecurity. https://doi.org/10.1002/9781119681427
  • EMarketer, & Insider Intelligence. (April 13, 2022). Number of voice assistant users in the United States from 2017 to 2022 (in millions) [Gráfico].// Statista. https://www.sta-tista.com/statistics/1029573/us-voice-assistant-users/
  • Enge, Eric; Spencer, Stephan; Stricchiola, Jessie C. (2015).The Art of SEO: mastering search engine optimization. 3ªed.. O’Reilly Media, Inc, USA.
  • Enge, Eric (2017). Featured Snippets: New Insights, New Opportunities. Stone Temple Company Blog. https://www.stonetemple.com/featured-snippets-new-Insights-new-opportunities/
  • Epstein, Robert; Lee, Vivian; Mohr, Roger; Zankich, Vanessa R. (2022). The Answer Bot Effect (ABE): A powerful new form of influence made possible by intelligent personal assistants and search engines. //PLOS ONE.17:6, e0268081. https://doi.org/10.1371/journal.pone.0268081
  • Google (2023). Google Trend. https://trends.google.es/
  • Harto, Agus Budi (2019). Implementing Website Design Based on Search Engine Optimization (SEO) Checklist to IncreaseWeb Popularity. Journal of Applied Information, Communication and Technology, 6:2, 87–97. https://doi.org/10.33555/ejaict.v6i2.67Ishkin
  • Rand. (2019 Agosto 13). Less than half of Google searches now result in a click. // SparkToro. https://sparktoro.com/blog/less-than-half-of-google-searches-now-re-sult-in-a-click/
  • Khashabi, Daniel; Ng, Amos; Khot, Tushar; Sabharwal, As-hish; Hajishirzi, Hannaneh; Callison-Burch, Chris (2021). GooAQ: Open Question Answering with Diverse Answer Types. // Findings of the Association for Computational Linguistics: EMNLP 2021, 421–433. https://doi.org/10.18653/v1/2021.findings-emnlp.38
  • Killoran, John B. (2013). How to Use Search Engine Optimization Techniques to Increase Website Visibility. // IEEE Transactions on Professional Communication, 56:1, 50–66. https://doi.org/10.1109/TPC.2012.2237255
  • Lewandowski, Dirk; Drechsler, Jessica; Mach, Sonja (2012). Deriving query intents from web search engine queries. // Journal of the American Society for Information Science and Technology, 63:9, 1773–1788. https://doi.org/10.1002/asi.22706
  • Lurie, Emma; Mustafaraj, Eni (2018). Investigating the Effects of Google’s Search Engine Result Page in Evaluatingthe Credibility of Online News Sources. // Proceedings of the 10th ACM Conference on Web Science, 107–116. https://doi.org/10.1145/3201064.3201095
  • Mander, Jason; Buckle, Chase (2018). Voice Search. Insight Report 2018. // Global Web Index.https://www.insidemar-keting.eu/cdn/wp-content/uploads/2019/01/Voice-Search-global-web-indexreport.pdf
  • Miklošík, Andrej; Hlavatý, Ivan; Daňo, Ferdinand; Červenka, Peter (2016). Google Answer Box Keyword-related analysis. A case study. // European Journal of Science and Theology.12:5,185-194. http://www.ejst.tuiasi.ro/Fi-les/60/19_Miklosik%20et%20al.pdf
  • Miklosik, Andrej. (2019). Search Engine Marketing Strategies: Google AnswerBox-Related Search Visibility Factors.// Handbook of Research on Entrepreneurship and Marketing for Global Reach in the Digital Economy, edited by Luísa Cagica Carvalho y Pedro Isaías, Eds. Hershey, PA, USA: IGI Global, 2019.463-485. https://doi.org/10.4018/978-1-5225-6307-5.ch020
  • Mishra, Amit; Jain, Sanjay Kumar (2016). A survey on question answering systems with classification. // Journal of King Saud University -Computer and Information Scien-ces.28:3, 345-361.
  • Moldovan, Dan; Harabagiu, Sanda; Pasca, Marius; Mihalcea, Rada; Girju, Roxana; Goodrum, Richard; Rus, Vasile (2000). The structure and performance of an open-do-main question answering system. // Proceedings of the 38th Annual Meeting on Association for Computational Linguistics -ACL ’00, 563–570. https://doi.org/10.3115/1075218.1075289
  • Morato, Jorge; Sánchez-Cuadrado, Sonia; Moreno, Valentin; Moreiro, José. A. (2013). Evolución de los factores de po-sicionamiento web y adaptación de las herramientas de optimización. // Revista española de Documentación Científica.36:3, e018. https://doi.org/10.3989/redc.2013.3.956
  • Nayak, Pandu (2019). Understanding Searches Better Than Ever Before. // Google. https://blog.google/products/search/search-language-understanding-bert
  • Nayak, Pandu (2022). How AI powers great research results. // Google. https://blog.google/products/search/how-ai-po-wers-great-search-results/
  • Sánchez-Cuadrado, Sonia; Lloréns, Juan; Morato, Jorge; Hurtado, José. A. (2003). Extracción Automática de Relaciones Semánticas. 2da. Conferencia Iberoamericana// Sistemas, Cibernética e Informática. CISCI 2003. Orlando (Florida) 31 -2 de agosto de 2003. 265-268.
  • Singhal, Amit (2012). Introducing the knowledge graph: things, not strings. https://google-blog.blogspot.co.at/2012/05/introducing-knowledge-graph-things-not.html.
  • StatCounter. (abril 26, 2023). Worldwide desktop market share of leading search engines from January 2015 to March 2023 [Gráfica].// Statista. https://www.sta-tista.com/statistics/216573/worldwide-market-share-of-search-engines/
  • StatCounter. (mayo 10, 2022). Cuota de mercado de los principales motores de búsqueda online usados// España// 2021 [Gráfica].// Statista. https://es.statista.com/estadis-ticas/670092/cuota-de-mercado-de-los-motores-de-bus-queda-por-buscador-espana/
  • Strzelecki, Artur; Rutecka, Paulina (2019). The Snippets Taxonomy in Web Search Engines. // M. Pańkowska & K. Sandkuhl (Eds.).Perspectives in Business Informatics Research. 365, 177-188. Springer International Publishing. https://doi.org/10.1007/978-3-030-31143-8_13
  • Strzelecki, Artur; Rutecka, Paulina (2020a). Direct Answersin Google Search Results. // IEEE Access.8, 103642-103654. https://doi.org/10.1109/ACCESS.2020.2999160Strzelecki, Artur; Rutecka, Paulina (2020b). Featured Snippets Results in Google Web Search: An Exploratory Study. In Á. Rocha, J. L. Reis, M. K. Peter, & Z. Bogdanović (Eds.), Marketing and Smart Technologies. 9-18. Springer. https://doi.org/10.1007/978-981-15-1564-4_2
  • Sullivan, Danny (2018, enero 30). A reintroduction to Google’s featured snippets. Blog Google. Consultado 30/03/2023. [Online] Disponible https://blog.google/pro-ducts/search/reintroduction-googles-featured-snippets/
  • Trippas, Johanne R.; Spina, Damiano; Thomas, Paul; Sanderson, Mark; Joho, Hideo; Cavedon, Lawrence (2020). Towards a model for spoken conversational search. // Information Processing & Management.57:2, 102162. https://doi.org/10.1016/j.ipm.2019.102162
  • Wu, Zhijing; Sanderson, Mark; Cambazoglu, B. Barla; Croft, W. Bruce; Scholer, Falk (2020). Providing Direct Answers in Search Results: A Study of User Behavior. // Proceedings of the 29th ACM International Conference on Information & Knowledge Management.1635-1644. https://doi.org/10.1145/3340531.3412017
  • Yu, Liyang (2014). A developer's guide to the semantic web (Second). Springer Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43796-4
  • Zhao, Yiming; Zhang, Jin; Xia, Xue; Le, Taowen (2019). Evaluation of Google question-answering quality. // Library Hi Tech. 37:2, 308–324. https://doi.org/10.1108/LHT-10-2017-0218
  • Ziakis, Christos; Vlachopoulou, Maro; Kyrkoudis, Theodosios; Karagkiozidou, Makrina (2019).Important factors for im-proving Google search rank.// Future Internet.11:2, 32.https://doi.org/10.3390/fi11020032
Fonte de datos: Dialnet