Direct Answers in Google Search Results

Strzelecki, Artur; Rutecka, Paulina

doi:10.1109/access.2020.2999160

Cited by 15 publications

(9 citation statements)

References 45 publications

(60 reference statements)

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“…Una respuesta destacada o featured answer es un fragmento o resumen extraído del texto de una página web que responden de forma directa a una consulta ejecutada en el buscador (Miklosik, 2019;Strzelecki & Rutecka, 2020a). Los fragmentos destacados tratan de proporcionar una respuesta completa ya sea simple o con varios pasos o piezas de información (por ejemplo, respuestas a how to?).…”

Section: Featured Answerunclassified

“…Respecto al buscador, la percepción del usuario mejora con los resultados directos pues el acceso directo permite descartar cualquier otro resultado orgánico. Desde el punto de vista del recurso, las páginas web experimentan una mayor visibilidad y un aumento del tráfico (Strzelecki & Rutecka, 2020a;Duong, 2019), contribuyendo a mejorar su autoridad del dominio. Desde el punto de vista del usuario, algunos trabajos han estudiado cómo las respuestas enriquecidas condicionan a los internautas quienes tienden a sobrevalorar la confianza en un sitio web (Bernstein et al, 2012;Lurie & Mustafaraj, 2018).…”

Section: Selección De Rich Answersunclassified

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Análisis de respuestas enriquecidas en Google

Sánchez-Cuadrado

Morato²

2023

Scire

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En recuperación de información web, los motores de búsqueda como Google incluyen funcionalidades que devuelven respuestas directas a las consultas de los usuarios. Estas respuestas tratan de resolver una necesidad informativa y se conocen como rich answers. Para determinar cómo se presentan estos resultados y cómo afecta la optimización de los motores de búsqueda, se ha realizado un análisis de las respuestas directas destacadas que presenta Google. En este trabajo se han examinado preguntas de tipo informacional expresadas en lenguaje natural con los términos "what is". Se ha analizado el listado de los resultados para identificar las características de las respuestas directas. Además, se han explorado las estrategias SEO que puedan determinar la relevancia del fragmento respecto de la consulta. Con este trabajo se constata que la respuesta no se extrae necesariamente de forma literal de una página web y se comprueba que la solución a las preguntas puede proceder de varios recursos. Los fragmentos de respuesta directa y otros rich answers pueden llegar a ocupar cerca de la mitad de la página principal de resultados, cobrando un mayor protagonismo y desplazando al resto de los resultados orgánicos. Las respuestas directas proporcionan un cambio en los hábitos de búsqueda y un nuevo modo de navegar en la red basado en un sistema hiperenlazado de pregunta respuesta.

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Section: Featured Answerunclassified

Section: Selección De Rich Answersunclassified

Análisis de respuestas enriquecidas en Google

Sánchez-Cuadrado

Morato²

2023

Scire

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“…Over time, Google–emulated to some extent by other, less popular search engines–has introduced several types of answer boxes, among them: a rich answer box (a type of featured snippet that includes additional information such as a graph, table, image, or interactive tool), a news stories box, a knowledge box (often information from Wikipedia displayed in the upper-right-hand corner of the search results page), a box suggesting related searches, and so on [ 64 , 65 ]. Our focus, however, is on what Google calls the “featured snippet,” a relatively small box that is unlabeled and contains a simple answer to a user’s query [ 66 ].…”

Section: Introductionmentioning

confidence: 99%

“…In a study published in 2017, 12.3% of the 112 million search queries examined produced featured snippets, and the appearance of snippets reduced user clicks to the first search result from 26.0% to 19.6% [ 118 ]. A more recent study found that shorter phrases in a search bar are more likely to generate featured snippets [ 65 ], and featured snippet sources have been found to vary by location [ 119 ]. A 2019 study found significant liberal bias in Google’s news boxes [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

The Answer Bot Effect (ABE): A powerful new form of influence made possible by intelligent personal assistants and search engines

et al. 2022

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We introduce and quantify a relatively new form of influence: the Answer Bot Effect (ABE). In a 2015 report in PNAS, researchers demonstrated the power that biased search results have to shift opinions and voting preferences without people’s knowledge–by up to 80% in some demographic groups. They labeled this phenomenon the Search Engine Manipulation Effect (SEME), speculating that its power derives from the high level of trust people have in algorithmically-generated content. We now describe three experiments with a total of 1,736 US participants conducted to determine to what extent giving users “the answer”–either via an answer box at the top of a page of search results or via a vocal reply to a question posed to an intelligent personal assistant (IPA)–might also impact opinions and votes. Participants were first given basic information about two candidates running for prime minister of Australia (this, in order to assure that participants were “undecided”), then asked questions about their voting preferences, then given answers to questions they posed about the candidates–either with answer boxes or with vocal answers on an Alexa simulator–and then asked again about their voting preferences. The experiments were controlled, randomized, double-blind, and counterbalanced. Experiments 1 and 2 demonstrated that answer boxes can shift voting preferences by as much as 38.6% and that the appearance of an answer box can reduce search times and clicks on search results. Experiment 3 demonstrated that even a single question-and-answer interaction on an IPA can shift voting preferences by more than 40%. Multiple questions posed to an IPA leading to answers that all have the same bias can shift voting preferences by more than 65%. Simple masking procedures still produced large opinion shifts while reducing awareness of bias to close to zero. ABE poses a serious threat to both democracy and human autonomy because (a) it produces large shifts in opinions and voting preferences with little or no user awareness, (b) it is an ephemeral form of influence that leaves no paper trail, and (c) worldwide, it is controlled almost exclusively by just four American tech companies. ABE will become a greater threat as people increasingly rely on IPAs for answers.

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“…Therefore, we now have "Featured snippets" available on these major search engines. To date, 15% of results answering questions such as who -what -how -where contain featured snippets [25], [26].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Search Environments for Learning Contexts

Kameni¹,

Batchakui²,

Nkambou³

2022

International Journal on Advanced Science, Engineering and Information Technology

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This article proposes an improvement of search engines in a learning or training context. Indeed, the learner requests resources or learning content in a training or learning situation. The same goes for the trainer, who wishes to select the appropriate resources available to his learners. Unfortunately, existing search engines produce an enormous mass of content but sometimes do not match the learning context, thus causing an enormous loss of time for the learner or the teacher to find the appropriate resources among this important batch. Therefore, we suggest associating a complementary layer with search engines to extract the most relevant information related to learning or training situations from the engine results. For this purpose, an integrated filter eliminates irrelevant results to the current learning or training situation; and performs a weighted reclassification of these results based on Bloom's taxonomy. In terms of the HMI, this layer allows having more informative result snippets. The experimentation of this environment is based on Google APIs. According to the Bloom hierarchy, the classification of the user question and the classification of the search results are carried out from Natural Language Processing based on Logistic Regression of Machine Learning Algorithms. The result obtained presents an intuitively favorable environment for education, leading to the implementation of a specific search engine capable of collecting, storing, and indexing educational concepts in the next stage of this project. A project to empirically evaluate the results obtained is currently underway.

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Direct Answers in Google Search Results

Cited by 15 publications

References 45 publications

Análisis de respuestas enriquecidas en Google

Análisis de respuestas enriquecidas en Google

The Answer Bot Effect (ABE): A powerful new form of influence made possible by intelligent personal assistants and search engines

Optimization of Search Environments for Learning Contexts

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