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Companion Publication of the 10th ACM Conference on Web Science最新文献

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Web Research Ethics: Confidentiality, Consent, Data Integrity & More 网络研究伦理:保密性，同意，数据完整性等
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3329797
K. Kinder-Kurlanda, M. Zimmer
{"title":"Web Research Ethics: Confidentiality, Consent, Data Integrity & More","authors":"K. Kinder-Kurlanda, M. Zimmer","doi":"10.1145/3328413.3329797","DOIUrl":"https://doi.org/10.1145/3328413.3329797","url":null,"abstract":"Researchers studying the web find themselves immersed in a domain where information flows freely but is also potentially bound by contextual norms and expectations, where platforms may oscillate between open and closed information flows, and where data may be user-generated, filtered, algorithmically-processed, or proprietary. When using the internet as a tool or a space of research web scientists are confronted with a continuously expanding set of ethical dilemmas. Participants of the tutorial will actively engage with concrete example cases of common, not so common, tricky, interesting and puzzling ethical dilemmas. Some in-depth ethical thinking and theory, as well as very practical and creative solutions, will be explored. Participants will also have the chance to bring their own questions or ethical dilemmas to the workshop (it will be possible to 'submit' cases in advance to be discussed in an ethics 'clinic') for discussion and help to find solutions.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131456439","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}
引用次数: 0
Search and Justification Behavior During Multimedia Web Search for Procedural Knowledge 多媒体网络程序性知识搜索中的搜索与正当化行为
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3329405
Georg Pardi, Yvonne Kammerer, Peter Gerjets
{"title":"Search and Justification Behavior During Multimedia Web Search for Procedural Knowledge","authors":"Georg Pardi, Yvonne Kammerer, Peter Gerjets","doi":"10.1145/3328413.3329405","DOIUrl":"https://doi.org/10.1145/3328413.3329405","url":null,"abstract":"In an eye-tracking study, N = 38 participants performed two procedural-knowledge search tasks by using a mockup multimedia search engine results page (SERP). By presenting both conventional websites and videos as results on the SERP, we aimed at examining the role of the modality of information resources in individuals' retrieval behavior as well in their final recommendation of one most suitable information resource. Across both tasks, the results of this study indicate that participants who finally recommended a video resource spent a greater proportion of time inspecting video results on the SERP as well as on the video resources themselves. Furthermore, participants' written justifications for the recommended information resource revealed that in both tasks about one third of the participants mentioned the modality of the information resource to justify their recommendation decision. Our findings indicate that the modality of information resources at least to some extent plays a role during web search for procedural learning resources.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123553443","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}
引用次数: 4
Understanding Demographic Bias and Representation in Social Media Health Data 了解社会媒体健康数据中的人口统计学偏差和代表性
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3328415
Nina L. Cesare, Christan Earl Grant, E. Nsoesie
{"title":"Understanding Demographic Bias and Representation in Social Media Health Data","authors":"Nina L. Cesare, Christan Earl Grant, E. Nsoesie","doi":"10.1145/3328413.3328415","DOIUrl":"https://doi.org/10.1145/3328413.3328415","url":null,"abstract":"Text, images, geotags and other data from social media sites lend researchers a unique window into population health trends and disease spread. While these data provide the opportunity to track and measure health outcomes across geographic regions, over extended periods of time, and through complex social networks, they also present challenges. Most notably, these data carry significant biases due to demographic differences in who chooses to use each platform, and what they choose to share. While several publications have discussed the limitations of leveraging social media data for public health research, the amount of literature systematically investigating their demographic bias and exploring mitigation strategies is limited and ripe for interdisciplinary contributions. In this discussion paper, we highlight that understanding the strengths and limitations of these data sources would enable a rigorous assessment of their usefulness for public health research and provide a means for quantifying uncertainty in research findings.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123098803","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}
引用次数: 11
Online Interactive Experiments on Networks 网络上的在线交互实验
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3329795
M. Mosleh
{"title":"Online Interactive Experiments on Networks","authors":"M. Mosleh","doi":"10.1145/3328413.3329795","DOIUrl":"https://doi.org/10.1145/3328413.3329795","url":null,"abstract":"Conducting human experiments using crowdsourcing platforms, such as Amazon Mechanical Turk, has made it possible to collect a much larger amount of experimental data in a much shorter period of time relative to what was possible in traditional physical lab settings. This has provided a new suite of methods for conducting randomized experiments in socio-technical systems, allowing for straightforward causal inference [1-4]. However, using crowdsourcing platforms to experimentally study real-time interactions between individuals presents numerous practical challenges. These studies need fairly large groups of subjects to be present simultaneously in each session, and outcomes typically occur at the level of the group (i.e., session) rather than the individual. Yet most crowdsourcing platforms are not designed to facilitate simultaneous structured interactions between subjects. Thus, it can be difficult (and expensive) to recruit enough participants to achieve a sufficient degree of statistical power (especially for session-level outcomes). In this tutorial, we will discuss best practices for designing and conducting online social network experiments where human subjects (and programmed bots) interact simultaneously within a specified network structure. We will show how the experimental design can be informed by computational models in an iterative process (i.e., using experimental data to calibrate the computational model and use the computational model to optimize the design and find the right parameters for the experiments). We will also introduce additional tools/platforms that facilitate conducting such studies and walk the audience through the implementation steps of a typical experiment on networks using customized and publicly available software.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438717","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}
引用次数: 0
Institutional Repositories as a Data Trust Infrastructure 作为数据信任基础设施的机构存储库
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3329402
Arwah Alsaad, K. O’Hara, Les Carr
{"title":"Institutional Repositories as a Data Trust Infrastructure","authors":"Arwah Alsaad, K. O’Hara, Les Carr","doi":"10.1145/3328413.3329402","DOIUrl":"https://doi.org/10.1145/3328413.3329402","url":null,"abstract":"This paper examines the potential use of data trusts to solve the problem of data sharing in multi-partner research activities and proposes the institutional repository as a candidate technology for data trust infrastructure.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116613362","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}
引用次数: 4
Handling Web Bias 2019: Chairs' Welcome and Workshop Summary 处理网络偏见2019:主席欢迎和研讨会总结
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3328417
R. Baeza-Yates, Jeanna Neefe Matthews
{"title":"Handling Web Bias 2019: Chairs' Welcome and Workshop Summary","authors":"R. Baeza-Yates, Jeanna Neefe Matthews","doi":"10.1145/3328413.3328417","DOIUrl":"https://doi.org/10.1145/3328413.3328417","url":null,"abstract":"A key aspect of the Web Science conference is exploring the ethical challenges of technologies, data, algorithms, platforms, and people in the Web as well as detecting, preventing and predicting anomalies in web data including algorithmic and data biases. Handling Web Bias (HWB) is a new workshop focusing on best practices for identifying and handling web bias. Awareness of the problems of algorithmic and data bias has been growing but even with careful review of the algorithms and data sets, it may not be possible to delete all unwanted bias, particularly when systems learn from historical data that encodes cultural biases. This workshop will take a rich and cross-domain approach to this complicated problem, providing a venue for researchers to move beyond awareness of the problem of algorithmic and data bias to focus on practical strategies for handling it.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126381264","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}
引用次数: 1
LILE2019
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-06-26 DOI: 10.1145/3328413.3329404
Ran Yu, Mathieu d'Aquin, D. Gašević, J. Kimmerle, E. Herder, Ralph Ewerth
{"title":"LILE2019","authors":"Ran Yu, Mathieu d'Aquin, D. Gašević, J. Kimmerle, E. Herder, Ralph Ewerth","doi":"10.1145/3328413.3329404","DOIUrl":"https://doi.org/10.1145/3328413.3329404","url":null,"abstract":"The purpose of the LILE2019 workshop is to provide an interdisciplinary forum for researchers and practitioners who make innovative use of Web data for educational purposes, spanning areas such as learning analytics, Web mining, data and Web science, psychology and the social sciences. The previous editions of the LILE workshop were successfully held at the ESWC, WWW, ISWC and WebSci conferences. LILE2019 consists of keynotes, presentations of accepted papers and posters and discussion.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127181331","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}
引用次数: 1
On Bias in Social Reviews of University Courses 论大学课程社会评价中的偏见
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 2019-05-06 DOI: 10.1145/3328413.3328416
Taha Hassan
{"title":"On Bias in Social Reviews of University Courses","authors":"Taha Hassan","doi":"10.1145/3328413.3328416","DOIUrl":"https://doi.org/10.1145/3328413.3328416","url":null,"abstract":"University course ranking forums are a popular means of disseminating information about satisfaction with the quality of course content and instruction, especially with undergraduate students. A variety of policy decisions by university administrators, instructional designers and teaching staff affect how students perceive the efficacy of pedagogies employed in a given course, in class and online. While there is a large body of research on qualitative driving factors behind the use of academic rating sites, there is little investigation of the (potential) implicit student bias on said forums towards desirable course outcomes at the institution level. To that end, we examine the connection between course outcomes (student-reported GPA) and the overall ranking of the primary course instructor, as well as rating disparity by nature of course outcomes, for several hundred courses taught at Virginia Tech based on data collected from a popular academic rating forum. We also replicate our analysis for several public universities across the US. Our experiments indicate that there is a discernible albeit complex bias towards course outcomes in the professor ratings registered by students.","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124126115","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}
引用次数: 4
Companion Publication of the 10th ACM Conference on Web Science 第十届ACM网络科学会议配套出版物
Companion Publication of the 10th ACM Conference on Web Science Pub Date : 1900-01-01 DOI: 10.1145/3328413
{"title":"Companion Publication of the 10th ACM Conference on Web Science","authors":"","doi":"10.1145/3328413","DOIUrl":"https://doi.org/10.1145/3328413","url":null,"abstract":"","PeriodicalId":102426,"journal":{"name":"Companion Publication of the 10th ACM Conference on Web Science","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134147943","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}
引用次数: 0
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