Dominique Kelly, Yimin Chen, Sarah E. Cornwell, Nicole S. Delellis, Alex Mayhew, Sodiq Onaolapo, Victoria L. Rubin
{"title":"必应聊天:搜索引擎的未来?","authors":"Dominique Kelly, Yimin Chen, Sarah E. Cornwell, Nicole S. Delellis, Alex Mayhew, Sodiq Onaolapo, Victoria L. Rubin","doi":"10.1002/pra2.927","DOIUrl":null,"url":null,"abstract":"ABSTRACT Introduced by Microsoft in February 2023, Bing Chat is a feature of the Bing search engine that integrates an OpenAI large language model (LLM) customised for search (Mehdi, 2023a). This poster compares the outputs of Bing Chat and a standard existing search engine (DuckDuckGo) in response to identical keyword queries and corresponding natural language (NL) questions. Specifically, we examined: (1) the length of Bing Chat's responses and DuckDuckGo's first page of search results, by number of website links; and, (2) the length of Bing Chat's textual summaries, by number of website links. We found that, on average, significantly fewer websites were linked to in Bing Chat's responses compared to DuckDuckGo's search results. Our findings have important implications for website operators, who may receive less traffic and ad revenue if LLM‐enabled search engines are widely adopted in the future. Human‐Computer Interaction (HCI) will inevitably face the need for more research on human information behaviours adaptations in response to the changing search paradigm.","PeriodicalId":37833,"journal":{"name":"Proceedings of the Association for Information Science and Technology","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Bing Chat: The Future of Search Engines?\",\"authors\":\"Dominique Kelly, Yimin Chen, Sarah E. Cornwell, Nicole S. Delellis, Alex Mayhew, Sodiq Onaolapo, Victoria L. Rubin\",\"doi\":\"10.1002/pra2.927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Introduced by Microsoft in February 2023, Bing Chat is a feature of the Bing search engine that integrates an OpenAI large language model (LLM) customised for search (Mehdi, 2023a). This poster compares the outputs of Bing Chat and a standard existing search engine (DuckDuckGo) in response to identical keyword queries and corresponding natural language (NL) questions. Specifically, we examined: (1) the length of Bing Chat's responses and DuckDuckGo's first page of search results, by number of website links; and, (2) the length of Bing Chat's textual summaries, by number of website links. We found that, on average, significantly fewer websites were linked to in Bing Chat's responses compared to DuckDuckGo's search results. Our findings have important implications for website operators, who may receive less traffic and ad revenue if LLM‐enabled search engines are widely adopted in the future. Human‐Computer Interaction (HCI) will inevitably face the need for more research on human information behaviours adaptations in response to the changing search paradigm.\",\"PeriodicalId\":37833,\"journal\":{\"name\":\"Proceedings of the Association for Information Science and Technology\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Association for Information Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/pra2.927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Association for Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/pra2.927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
ABSTRACT Introduced by Microsoft in February 2023, Bing Chat is a feature of the Bing search engine that integrates an OpenAI large language model (LLM) customised for search (Mehdi, 2023a). This poster compares the outputs of Bing Chat and a standard existing search engine (DuckDuckGo) in response to identical keyword queries and corresponding natural language (NL) questions. Specifically, we examined: (1) the length of Bing Chat's responses and DuckDuckGo's first page of search results, by number of website links; and, (2) the length of Bing Chat's textual summaries, by number of website links. We found that, on average, significantly fewer websites were linked to in Bing Chat's responses compared to DuckDuckGo's search results. Our findings have important implications for website operators, who may receive less traffic and ad revenue if LLM‐enabled search engines are widely adopted in the future. Human‐Computer Interaction (HCI) will inevitably face the need for more research on human information behaviours adaptations in response to the changing search paradigm.
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