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This research aims to explore the integration of Bing Chat, an artificial intelligence (AI)-powered conversational assistant, into academic libraries and its potential impact on reference services.

This study analyzes existing literature to investigate the integration of Bing Chat in academic libraries. This research focuses on its features, capabilities and implications for enhancing user experiences and addressing information needs.

The findings highlight that Bing Chat’s conversational interface facilitates more dynamic and context-aware reference interactions, fostering user empowerment and personalized learning pathways. The integration of Bing Chat with existing library resources enhances resource discovery, navigational assistance and engagement with visual content. However, challenges related to accuracy, privacy and algorithmic bias require careful consideration.

This research contributes to the literature by providing an in-depth exploration of Bing Chat’s integration into academic libraries, emphasizing its transformative potential for reference services. This study addresses ethical and social dimensions associated with AI-driven tools in library environments, offering insights into ensuring fairness, privacy and user trust.

The purpose of this paper is to analyze the readability and level of word complexity of search engine results pages (SERPs) snippets and associated web pages between Google and Bing.

The authors employed the Readability Test Tool to analyze the readability and word complexity of 3,000 SERPs snippets and 3,000 associated pages in Google and Bing retrieved on 150 search queries issued by middle school children.

A significant difference was found in the readability of SERPs snippets and associated web pages between Google and Bing. A significant difference was also observed in the number of complex words in snippets between the two engines but not in associated web pages. At the engine level, the readability of Google and Bing snippets was significantly higher than associated web pages. The readability of Google SERPs snippets was at a much higher level than those of Bing. The readability of snippets in both engines mismatched with the reading comprehension of children in grades 6–8.

The data corpus may be small. Analysis relied on quantitative measures.

Practitioners and other mediators should mitigate the readability issue in SERPs snippets. Researchers should consider text readability and word complexity simultaneously with other factors to obtain the nuanced understanding of young users’ web information behaviors. Additional theoretical and methodological implications are discussed.

This study measured the readability and the level of word complexity embedded in SERPs snippets and compared them to respective web pages in Google and Bing. Findings provide further evidence of the readability issue of SERPs snippets and the need to solve this issue through system design improvements.

The purpose of this study is to assess the retrieval performance of three search engines, i.e. Google, Yahoo and Bing for navigational queries using two important retrieval measures, i.e. precision and relative recall in the field of life science and biomedicine.

Top three search engines namely Google, Yahoo and Bing were selected on the basis of their ranking as per Alexa, an analytical tool that provides ranking of global websites. Furthermore, the scope of study was confined to those search engines having interface in English. Clarivate Analytics' Web of Science was used for the extraction of navigational queries in the field of life science and biomedicine. Navigational queries (classified as one-word, two-word and three-word queries) were extracted from the keywords of the papers representing the top 100 contributing authors in the select field. Keywords were also checked for the duplication. Two important evaluation parameters, i.e. precision and relative recall were used to calculate the performance of search engines on the navigational queries.

The mean precision for Google scores high (2.30) followed by Yahoo (2.29) and Bing (1.68), while mean relative recall also scores high for Google (0.36) followed by Yahoo (0.33) and Bing (0.31) respectively.

The study is of great help to the researchers and academia in determining the retrieval efficiency of Google, Yahoo and Bing in terms of navigational query execution in the field of life science and biomedicine. The study can help users to focus on various search processes and the query structuring and its execution across the select search engines for achieving desired result list in a professional search environment. The study can also act as a ready reference source for exploring navigational queries and how these queries can be managed in the context of information retrieval process. It will also help to showcase the retrieval efficiency of various search engines on the basis of subject diversity (life science and biomedicine) highlighting the same in terms of query intention.

Though many studies have been conducted highlighting the retrieval efficiency of search engines the current work is the first of its kind to study the retrieval effectiveness of Google, Yahoo and Bing on navigational queries in the field of life science and biomedicine. The study will help in understanding various methods and approaches to be adopted by the users for the navigational query execution across a professional search environment, i.e. “life science and biomedicine”

The purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator.

A sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017).

It has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP.

Future studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines.

Selecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies.

The findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines.

The website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date.

The purpose of this article is to explore the relationship between the attributes of Olympic mascots and their impact on sponsorship effectiveness. Based on a multiattribute model and the introduction of engagement theory and the meaning transfer model, this article uses the 2022 Beijing Winter Olympics mascot “Bing Dwen Dwen” as the research object to empirically analyze the effects and mechanisms of the mascot's attributes on preference, event engagement, sponsorship enterprise trust and sponsorship enterprise attitude, ultimately constructing a sponsorship effectiveness model.

The survey method was used to examine 238 respondents' emotions and attitudes towards companies participating in sponsoring Olympic mascots.

The study found that the main attributes of the mascot include visual and emotional factors, both of which have a positive impact on preference, with emotional factors having a greater influence than visual factors. Visual and emotional factors indirectly affect engagement through preference. Preference and engagement play a completely mediating role in the effect of mascot attributes on sponsorship enterprise trust and sponsorship enterprise attitude.

This study provides practical recommendations for managers to achieve marketing success in sports sponsorship through mascots.

This paper provides a measurement tool for the study of mascot attributes and important support for subsequent research in sponsorship marketing.

The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated: coverage of entity types, the extent of their support for list search services and the capabilities of their natural language query interfaces.

The authors manually submitted selected queries to these two semantic web search engines and evaluated the returned results. To test the coverage of entity types, the authors selected the entity types from Freebase database. To test the capabilities of natural language query interfaces, the authors used a manually developed query data set about US geography.

The results indicate that both semantic search engines cover only the very common entity types. In addition, the list search service is provided for a small percentage of entity types. Moreover, both search engines support queries with very limited complexity and with limited set of recognised terms.

Both companies are continually working to improve their semantic web search engines. Therefore, the findings show their capabilities at the time of conducting this research.

The results show that in the near future the authors can expect both semantic search engines to expand their entity databases and improve their natural language interfaces.

As far as the authors know, this is the first study evaluating any aspect of newly developing semantic web search engines. It shows the current capabilities and limitations of these semantic web search engines. It provides directions to researchers by pointing out the main problems for semantic web search engines.

There is an open discussion in the geographic information community about the use of digital libraries or search engines for the discovery of resources. Some researchers suggest that search engines are a feasible alternative for searching geographic web services based on anecdotal evidence. The purpose of this study is to measure the performance of Bing (formerly Microsoft Live Search), Google and Yahoo! in searching standardised XML documents that describe, identify and locate geographic web services.

The study performed an automated evaluation of three search engines using their application programming interfaces. The queries asked for XML documents describing geographic web services, and documents containing links to those documents. Relevant XML documents linked from the documents found in the search results were also included in the evaluation.

The study reveals that the discovery of geographic web services in search engines does not require the use of advanced search operators. Data collected suggest that a resource‐oriented search should combine simple queries to search engines with the exploration of the pages linked from the search results. Finally the study identifies Yahoo! as the best performer.

This is the first study that measures and compares the performance of major search engines in the discovery of geographic web services. Previous studies were focused on demonstrating the technical feasibility of the approach. The paper also reveals that some technical advances in search engines could harm resource‐oriented queries.

The purpose of this research project was to determine how the three biggest search engines interpret keyword stuffing as a negative design element.

This research was based on triangulation between scholar reporting, search engine claims, SEO practitioners and empirical evidence on the interpretation of keyword stuffing. Five websites with varying keyword densities were designed and submitted to Google, Yahoo! and Bing. Two phases of the experiment were done and the response of the search engines was recorded.

Scholars have indicated different views in respect of spamdexing, characterised by different keyword density measurements in the body text of a webpage. During both phases, almost all the test webpages, including the one with a 97.3 per cent keyword density, were indexed.

Only the three biggest search engines were considered, and monitoring was done for a set time only. The claims that high keyword densities will lead to blacklisting have been refuted.

Websites should be designed with high quality, well‐written content. Even though keyword stuffing is unlikely to lead to search engine penalties, it could deter human visitors and reduce website value.

After discussing the characteristics of text retrieval systems, their development is outlined. An explanation is given of the information requirements of lawyers in relation to legal databases. The work undertaken by the Norwegian Research Centre (NRCCL) is described. Details are given of the use made of STATUS and the redesigned version subsequently called NOVA*STATUS, which has been used to run various services as part of the NORIS (previously JURIS) research programme for text retrieval systems. Various research results from the NORIS work are described. Details are given of the controlled experiments in evaluating text retrieval systems performance and the ways of formulating searches. Results are discussed in terms of precision and recall. A particular feature of the investigations relate to the use of ranked output and the criteria for ranking. A new software package called SIFT is how being developed for use on a NOR minicomputer, in the light of the experiences with STATUS and the NORIS research results. 17 refs.

The purpose of this paper is to clarify how many removal requests are made, how often, and who makes these requests, as well as which websites are reported to search engines so they can be removed from the search results.

Undertakes a deep analysis of more than 3.2bn removed pages from Google’s search results requested by reporting organizations from 2011 to 2018 and over 460m removed pages from Bing’s search results requested by reporting organizations from 2015 to 2017. The paper focuses on pages that belong to the .pl country coded top-level domain (ccTLD).

Although the number of requests to remove data from search results has been growing year on year, fewer URLs have been reported in recent years. Some of the requests are, however, unjustified and are rejected by teams representing the search engines. In terms of reporting copyright violations, one company in particular stands out (AudioLock.Net), accounting for 28.1 percent of all reports sent to Google (the top ten companies combined were responsible for 61.3 percent of the total number of reports).

As not every request can be published, the study is based only what is publicly available. Also, the data assigned to Poland is only based on the ccTLD domain name (.pl); other domain extensions for Polish internet users were not considered.

This is first global analysis of data from transparency reports published by search engine companies as prior research has been based on specific notices.