Horatiu Bota, Adam Fourney, S. Dumais, T. L. Religa, Robert Rounthwaite
Complex software applications expose hundreds of commands to users through intricate menu hierarchies. One of the most popular productivity software suites, Microsoft Office, has recently developed functionality that allows users to issue free-form text queries to a search system to quickly find commands they want to execute, retrieve help documentation or access web results in a unified interface. In this paper, we analyze millions of search sessions originating from within Microsoft Office applications, collected over one month of activity, in an effort to characterize search behavior in productivity software. Our research brings together previous efforts in analyzing command usage in large-scale applications and efforts in understanding search behavior in environments other than the web. Our findings show that users engage primarily in command search, and that re-accessing commands through search is a frequent behavior. Our work represents the first large-scale analysis of search over command spaces and is an important first step in understanding how search systems integrated with productivity software can be successfully developed.
{"title":"Characterizing Search Behavior in Productivity Software","authors":"Horatiu Bota, Adam Fourney, S. Dumais, T. L. Religa, Robert Rounthwaite","doi":"10.1145/3176349.3176395","DOIUrl":"https://doi.org/10.1145/3176349.3176395","url":null,"abstract":"Complex software applications expose hundreds of commands to users through intricate menu hierarchies. One of the most popular productivity software suites, Microsoft Office, has recently developed functionality that allows users to issue free-form text queries to a search system to quickly find commands they want to execute, retrieve help documentation or access web results in a unified interface. In this paper, we analyze millions of search sessions originating from within Microsoft Office applications, collected over one month of activity, in an effort to characterize search behavior in productivity software. Our research brings together previous efforts in analyzing command usage in large-scale applications and efforts in understanding search behavior in environments other than the web. Our findings show that users engage primarily in command search, and that re-accessing commands through search is a frequent behavior. Our work represents the first large-scale analysis of search over command spaces and is an important first step in understanding how search systems integrated with productivity software can be successfully developed.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116679704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Relevance judgments are essential for designing information retrieval systems. Traditionally, judgments have been gathered via desktop interfaces. However, with the rise in popularity of smaller devices for information access, it has become imperative to investigate whether desktop based judgments are different from mobile judgments. Recently, user effort and document usefulness have also emerged as important dimensions to optimize and evaluate information retrieval systems. Since existing work is limited to desktops, it remains to be seen how these judgments are affected by user»s search device. In this paper, we address these shortcomings by collecting and analyzing relevance, usefulness and effort judgments on mobiles and desktops. Analysis of these judgments shows high agreement rate between desktop and mobile judges for relevance, followed by usefulness and findability. We also found that desktop judges are likely to spend more time and examine non-relevant/not-useful/difficult documents in greater depth compared to mobile judges. Based on our findings, we suggest that relevance judgments should be gathered via desktops and effort judgments should be collected on each device independently.
{"title":"Study of Relevance and Effort across Devices","authors":"Manisha Verma, Emine Yilmaz, Nick Craswell","doi":"10.1145/3176349.3176888","DOIUrl":"https://doi.org/10.1145/3176349.3176888","url":null,"abstract":"Relevance judgments are essential for designing information retrieval systems. Traditionally, judgments have been gathered via desktop interfaces. However, with the rise in popularity of smaller devices for information access, it has become imperative to investigate whether desktop based judgments are different from mobile judgments. Recently, user effort and document usefulness have also emerged as important dimensions to optimize and evaluate information retrieval systems. Since existing work is limited to desktops, it remains to be seen how these judgments are affected by user»s search device. In this paper, we address these shortcomings by collecting and analyzing relevance, usefulness and effort judgments on mobiles and desktops. Analysis of these judgments shows high agreement rate between desktop and mobile judges for relevance, followed by usefulness and findability. We also found that desktop judges are likely to spend more time and examine non-relevant/not-useful/difficult documents in greater depth compared to mobile judges. Based on our findings, we suggest that relevance judgments should be gathered via desktops and effort judgments should be collected on each device independently.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117233798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ion Madrazo Azpiazu, Nevena Dragovic, Oghenemaro Anuyah, M. S. Pera
Popular search engines are usually tuned to satisfy the information needs of a general audience. As a result, non-traditional, yet active groups of users, such as children, experience challenges composing queries that can lead them to the retrieval of adequate results. To aid young users in formulating keyword queries that can facilitate their information-seeking process, we introduce ReQuIK, a multi-perspective query suggestion system for children. ReQuIK informs its suggestion process by applying (i) a strategy based on search intent to capture the purpose of a query, (ii) a ranking strategy based on a wide and deep neural network that considers both raw text and traits commonly associated with kid-related queries, (iii) a filtering strategy based on the readability levels of documents potentially retrieved by a query to favor suggestions that trigger the retrieval of documents matching children»s reading skills, and (iv) a content-similarity strategy to ensure diversity among suggestions. For assessing the quality of the system, we conducted initial offline and online experiments based on 591 queries written by 97 children, ages 6 to 13. The results of this assessment verified the correctness of ReQuIK»s recommendation strategy, the fact that it provides suggestions that appeal to children and ReQuIK»s ability to recommend queries that lead to the retrieval of materials with readability levels that correlate with children»s reading skills.
{"title":"Looking for the Movie Seven or Sven from the Movie Frozen?: A Multi-perspective Strategy for Recommending Queries for Children","authors":"Ion Madrazo Azpiazu, Nevena Dragovic, Oghenemaro Anuyah, M. S. Pera","doi":"10.1145/3176349.3176379","DOIUrl":"https://doi.org/10.1145/3176349.3176379","url":null,"abstract":"Popular search engines are usually tuned to satisfy the information needs of a general audience. As a result, non-traditional, yet active groups of users, such as children, experience challenges composing queries that can lead them to the retrieval of adequate results. To aid young users in formulating keyword queries that can facilitate their information-seeking process, we introduce ReQuIK, a multi-perspective query suggestion system for children. ReQuIK informs its suggestion process by applying (i) a strategy based on search intent to capture the purpose of a query, (ii) a ranking strategy based on a wide and deep neural network that considers both raw text and traits commonly associated with kid-related queries, (iii) a filtering strategy based on the readability levels of documents potentially retrieved by a query to favor suggestions that trigger the retrieval of documents matching children»s reading skills, and (iv) a content-similarity strategy to ensure diversity among suggestions. For assessing the quality of the system, we conducted initial offline and online experiments based on 591 queries written by 97 children, ages 6 to 13. The results of this assessment verified the correctness of ReQuIK»s recommendation strategy, the fact that it provides suggestions that appeal to children and ReQuIK»s ability to recommend queries that lead to the retrieval of materials with readability levels that correlate with children»s reading skills.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124505295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tarfah Alrashed, Ahmed Hassan Awadallah, S. Dumais
Email continues to be one of the most important means of online communication, leading to a number of challenges related to information overload and email management. To better understand email management practices in detail, we examine the distribution of visits to emails over time. During their lifetime, emails may be visited one or more times, and with each visit different actions may be taken. Emails that are revisited over time are especially interesting because they represent an opportunity to improve email management and search. In this paper, we present a large-scale log analysis of email revisitation, the activities that people perform on revisited email messages (e.g. responding to, organizing or deleting messages, and opening attachments), and the strategies they use to go back to these emails. We find that most emails have a short lifetime, with more than 33% having a lifetime of less than 5 minutes. We also find that deleting is the most common action taken on messages visited once, and that responding and organizing are more common for messages visited more than once. We complement the log analysis with a survey to understand the motivation behind revisits and the types of emails that are revisited. The survey results show that 73% of the visits are to find information (e.g. a link or document, instructions to perform a task, or answers to questions), while 20% of revisits are to respond to the email. Our findings have implications for designing email clients and intelligent agents that support both short- and long-term revisitation patterns.
{"title":"The Lifetime of Email Messages: A Large-Scale Analysis of Email Revisitation","authors":"Tarfah Alrashed, Ahmed Hassan Awadallah, S. Dumais","doi":"10.1145/3176349.3176398","DOIUrl":"https://doi.org/10.1145/3176349.3176398","url":null,"abstract":"Email continues to be one of the most important means of online communication, leading to a number of challenges related to information overload and email management. To better understand email management practices in detail, we examine the distribution of visits to emails over time. During their lifetime, emails may be visited one or more times, and with each visit different actions may be taken. Emails that are revisited over time are especially interesting because they represent an opportunity to improve email management and search. In this paper, we present a large-scale log analysis of email revisitation, the activities that people perform on revisited email messages (e.g. responding to, organizing or deleting messages, and opening attachments), and the strategies they use to go back to these emails. We find that most emails have a short lifetime, with more than 33% having a lifetime of less than 5 minutes. We also find that deleting is the most common action taken on messages visited once, and that responding and organizing are more common for messages visited more than once. We complement the log analysis with a survey to understand the motivation behind revisits and the types of emails that are revisited. The survey results show that 73% of the visits are to find information (e.g. a link or document, instructions to perform a task, or answers to questions), while 20% of revisits are to respond to the email. Our findings have implications for designing email clients and intelligent agents that support both short- and long-term revisitation patterns.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134496680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The detection of echo chambers and information bubbles is becoming increasingly relevant in this era of polarized information. It may be possible to evaluate information trustworthiness by examining the behavior of individuals in belief space rather than evaluating the information itself, which is a harder problem. To explore this, I propose to research a model for information retrieval that integrates two levels of information interaction. On the individual level, I leverage Munson and Resnick»s diversity-seeker, confirmer, and avoider patterns. At a group level, I integrate individual behaviors according to Moskivici»s work on crowd polarization. These perspectives have been integrated in a simulation that employs insights from animal collective behavior to model agent groups, which enable the systematic exploration of belief navigation behaviors that can be detected algorithmically. Viewing information retrieval from the perspective of belief spaces may shed light on current practices and lay out consideration for future design work.
{"title":"With Maps and Mobs: Searching for Trustworthiness using Belief Spaces","authors":"Philip G. Feldman","doi":"10.1145/3176349.3176353","DOIUrl":"https://doi.org/10.1145/3176349.3176353","url":null,"abstract":"The detection of echo chambers and information bubbles is becoming increasingly relevant in this era of polarized information. It may be possible to evaluate information trustworthiness by examining the behavior of individuals in belief space rather than evaluating the information itself, which is a harder problem. To explore this, I propose to research a model for information retrieval that integrates two levels of information interaction. On the individual level, I leverage Munson and Resnick»s diversity-seeker, confirmer, and avoider patterns. At a group level, I integrate individual behaviors according to Moskivici»s work on crowd polarization. These perspectives have been integrated in a simulation that employs insights from animal collective behavior to model agent groups, which enable the systematic exploration of belief navigation behaviors that can be detected algorithmically. Viewing information retrieval from the perspective of belief spaces may shed light on current practices and lay out consideration for future design work.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130511812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we present work-in-progress results from the stimulated recall portion of a U.S.-based lab study that investigated the influence of financial knowledge and cognitive abilities on the search performance, relevance assessments, and mental workload of adults searching the Internet for personal finance topics. Participants were asked to retrospectively think aloud while viewing screen recordings of one of their search tasks. Qualitative, inductive coding was applied to transcribed interviews. An early theme about government websites and information emerged in the data analysis and that is the topic of this paper. For all three tasks, participants prioritized and valued information from U.S. government websites over that of commercial websites, which seems to contradict recent national surveys indicating low levels of trust in government information sources and the government in general. Our findings suggest that for certain topics, especially those associated with high levels of uncertainty, people might resort to more basic search and evaluation behaviors.
{"title":"Strategies for Finding and Evaluating Information about Personal Finance Topics: The Role of Government Information","authors":"Kathy Brennan, D. Kelly","doi":"10.1145/3176349.3176883","DOIUrl":"https://doi.org/10.1145/3176349.3176883","url":null,"abstract":"In this paper, we present work-in-progress results from the stimulated recall portion of a U.S.-based lab study that investigated the influence of financial knowledge and cognitive abilities on the search performance, relevance assessments, and mental workload of adults searching the Internet for personal finance topics. Participants were asked to retrospectively think aloud while viewing screen recordings of one of their search tasks. Qualitative, inductive coding was applied to transcribed interviews. An early theme about government websites and information emerged in the data analysis and that is the topic of this paper. For all three tasks, participants prioritized and valued information from U.S. government websites over that of commercial websites, which seems to contradict recent national surveys indicating low levels of trust in government information sources and the government in general. Our findings suggest that for certain topics, especially those associated with high levels of uncertainty, people might resort to more basic search and evaluation behaviors.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132288272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Search, especially library search, is a distinct part of the research process which can be taught and supported separately from the scholarly processes of knowledge creation. We interviewed eight early career researchers (ECRs) composed of doctoral students or recent graduates about their overall scholarly workflows including not only search but also social networking around scholarly information and production of scholarly works. Evidence suggests that search itself is less discrete and library-centric than prior models may have suggested, and that students use both social resources and non-library technologies to discover and locate scholarly works. We argue that taking a workflow-centric and collaboration-centric view, rather than a search-centric view, should inform design of tools and training for search of scholarly resources.
{"title":"A Study of Search Practices in Doctoral Student Scholarly Workflows","authors":"S. Ince, C. Hoadley, P. Kirschner","doi":"10.1145/3176349.3176877","DOIUrl":"https://doi.org/10.1145/3176349.3176877","url":null,"abstract":"Search, especially library search, is a distinct part of the research process which can be taught and supported separately from the scholarly processes of knowledge creation. We interviewed eight early career researchers (ECRs) composed of doctoral students or recent graduates about their overall scholarly workflows including not only search but also social networking around scholarly information and production of scholarly works. Evidence suggests that search itself is less discrete and library-centric than prior models may have suggested, and that students use both social resources and non-library technologies to discover and locate scholarly works. We argue that taking a workflow-centric and collaboration-centric view, rather than a search-centric view, should inform design of tools and training for search of scholarly resources.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133717074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Hienert, M. Mitsui, Philipp Mayr, C. Shah, N. Belkin
When users are looking for information on the Web, they show different behavior for different task types, e.g., for fact finding vs. information gathering tasks. For example, related work in this area has investigated how this behavior can be measured and applied to distinguish between easy and difficult tasks. In this work, we look at the searcher's behavior in the domain of journalism for four different task types, and additionally, for two different topics in each task type. Search behavior is measured with a number of session variables and correlated to subjective measures such as task difficulty, task success and the usefulness of documents. We acknowledge prior results in this area that task difficulty is correlated to user effort and that easy and difficult tasks are distinguishable by session variables. However, in this work, we emphasize the role of the task topic - in and of itself - over parameters such as the search results and read content pages, dwell times, session variables and subjective measures such as task difficulty or task success. With this knowledge researchers should give more attention to the task topic as an important influence factor for user behavior.
{"title":"The Role of the Task Topic in Web Search of Different Task Types","authors":"Daniel Hienert, M. Mitsui, Philipp Mayr, C. Shah, N. Belkin","doi":"10.1145/3176349.3176382","DOIUrl":"https://doi.org/10.1145/3176349.3176382","url":null,"abstract":"When users are looking for information on the Web, they show different behavior for different task types, e.g., for fact finding vs. information gathering tasks. For example, related work in this area has investigated how this behavior can be measured and applied to distinguish between easy and difficult tasks. In this work, we look at the searcher's behavior in the domain of journalism for four different task types, and additionally, for two different topics in each task type. Search behavior is measured with a number of session variables and correlated to subjective measures such as task difficulty, task success and the usefulness of documents. We acknowledge prior results in this area that task difficulty is correlated to user effort and that easy and difficult tasks are distinguishable by session variables. However, in this work, we emphasize the role of the task topic - in and of itself - over parameters such as the search results and read content pages, dwell times, session variables and subjective measures such as task difficulty or task success. With this knowledge researchers should give more attention to the task topic as an important influence factor for user behavior.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125100784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this demo, we present Coagmento, a Web-based, open-source tool for information seeking projects that collects information for individuals and groups and helps facilitate collaborative information seeking. Coagmento has been used in information retrieval and human-computer interaction studies to investigate individual and group information seeking behaviors in a lab or a field setting. In this demo, we discuss what Coagmento is, its past uses in prior studies, and its present state. We also discuss current work in progress. With Coagmento recently passing its 10th anniversary, we discuss our intention to make it a tool that is easy to configure for a human information behavior researcher with little programming skill.
{"title":"Coagmento: Past, Present, and Future of an Individual and Collaborative Information Seeking Platform","authors":"M. Mitsui, Jiqun Liu, C. Shah","doi":"10.1145/3176349.3176896","DOIUrl":"https://doi.org/10.1145/3176349.3176896","url":null,"abstract":"In this demo, we present Coagmento, a Web-based, open-source tool for information seeking projects that collects information for individuals and groups and helps facilitate collaborative information seeking. Coagmento has been used in information retrieval and human-computer interaction studies to investigate individual and group information seeking behaviors in a lab or a field setting. In this demo, we discuss what Coagmento is, its past uses in prior studies, and its present state. We also discuss current work in progress. With Coagmento recently passing its 10th anniversary, we discuss our intention to make it a tool that is easy to configure for a human information behavior researcher with little programming skill.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128380069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Web search is frequently used by people to acquire new knowledge and to satisfy learning-related objectives, but little is known about how a user»s knowledge evolves through the course of a search session. We present a study addressing the knowledge gain of users in informational search sessions. Using crowdsourcing, we recruited 500 distinct users and orchestrated real-world search sessions spanning 10 different topics and information needs. By using scientifically formulated knowledge tests we calibrated the knowledge of users before and after their search sessions, quantifying their knowledge gain. We investigated the impact of information needs on the search behavior and knowledge gain of users, revealing a significant effect of information need on user queries and navigational patterns, but no direct effect on the knowledge gain. Users on average exhibited a higher knowledge gain through search sessions pertaining to topics they were less familiar with. Our findings in this paper contribute important ground work towards advancing current research in understanding user knowledge gain through web search sessions.
{"title":"Analyzing Knowledge Gain of Users in Informational Search Sessions on the Web","authors":"U. Gadiraju, Ran Yu, S. Dietze, Peter Holtz","doi":"10.1145/3176349.3176381","DOIUrl":"https://doi.org/10.1145/3176349.3176381","url":null,"abstract":"Web search is frequently used by people to acquire new knowledge and to satisfy learning-related objectives, but little is known about how a user»s knowledge evolves through the course of a search session. We present a study addressing the knowledge gain of users in informational search sessions. Using crowdsourcing, we recruited 500 distinct users and orchestrated real-world search sessions spanning 10 different topics and information needs. By using scientifically formulated knowledge tests we calibrated the knowledge of users before and after their search sessions, quantifying their knowledge gain. We investigated the impact of information needs on the search behavior and knowledge gain of users, revealing a significant effect of information need on user queries and navigational patterns, but no direct effect on the knowledge gain. Users on average exhibited a higher knowledge gain through search sessions pertaining to topics they were less familiar with. Our findings in this paper contribute important ground work towards advancing current research in understanding user knowledge gain through web search sessions.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128473593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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