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\n  \n 2023\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n \n Understanding Privacy in Virtual Reality Classrooms: A Contextual Integrity Perspective.\n \n \n \n \n\n\n \n Brehm, K.; and Shvartzhnaider, Y.\n\n\n \n\n\n\n IEEE Security & Privacy,2–11. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"UnderstandingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{brehm_understanding_2023,\n\ttitle = {Understanding {Privacy} in {Virtual} {Reality} {Classrooms}: {A} {Contextual} {Integrity} {Perspective}},\n\tissn = {1540-7993, 1558-4046},\n\tshorttitle = {Understanding {Privacy} in {Virtual} {Reality} {Classrooms}},\n\turl = {https://ieeexplore.ieee.org/document/10352441/},\n\tdoi = {10.1109/MSEC.2023.3336802},\n\turldate = {2023-12-12},\n\tjournal = {IEEE Security \\& Privacy},\n\tauthor = {Brehm, Karoline and Shvartzhnaider, Yan},\n\tyear = {2023},\n\tpages = {2--11},\n}\n\n
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\n \n\n \n \n \n \n \n \n Beyond the text: Analysis of privacy statements through syntactic and semantic role labeling.\n \n \n \n \n\n\n \n Shvartzshanider, Y.; Balashankar, A.; Wies, T.; and Subramanian, L.\n\n\n \n\n\n\n In Proceedings of the natural legal language processing workshop 2023, pages 85–98, Singapore, December 2023. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"BeyondPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{shvartzshanider-etal-2023-beyond,\n\taddress = {Singapore},\n\ttitle = {Beyond the text: {Analysis} of privacy statements through syntactic and semantic role labeling},\n\turl = {https://aclanthology.org/2023.nllp-1.10},\n\tabstract = {This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity (CI), an established social theory framework for reasoning about privacy norms. Through extensive experiments, we further show that incorporating CI-based domain-specific knowledge into a BERT-based SRL model results in the highest precision and recall, achieving an F1 score of 84\\%. With our work, we would like to motivate new research in building NLP applications for the privacy domain.},\n\tbooktitle = {Proceedings of the natural legal language processing workshop 2023},\n\tpublisher = {Association for Computational Linguistics},\n\tauthor = {Shvartzshanider, Yan and Balashankar, Ananth and Wies, Thomas and Subramanian, Lakshminarayanan},\n\tmonth = dec,\n\tyear = {2023},\n\tpages = {85--98},\n}\n\n
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\n This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity (CI), an established social theory framework for reasoning about privacy norms. Through extensive experiments, we further show that incorporating CI-based domain-specific knowledge into a BERT-based SRL model results in the highest precision and recall, achieving an F1 score of 84%. With our work, we would like to motivate new research in building NLP applications for the privacy domain.\n
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\n \n\n \n \n \n \n \n \n Private attributes: The meanings and mechanisms of “privacy-preserving” adtech.\n \n \n \n \n\n\n \n McGuigan, L.; Sivan-Sevilla, I.; Parham, P.; and Shvartzshnaider, Y.\n\n\n \n\n\n\n New Media & Society, 0(0). 2023.\n \n\n\n\n
\n\n\n\n \n \n \"PrivatePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{mcguigan_private_2023,\n\ttitle = {Private attributes: {The} meanings and mechanisms of “privacy-preserving” adtech},\n\tvolume = {0},\n\turl = {https://doi.org/10.1177/14614448231213267},\n\tdoi = {10.1177/14614448231213267},\n\tlanguage = {en},\n\tnumber = {0},\n\tjournal = {New Media \\& Society},\n\tauthor = {McGuigan, L. and Sivan-Sevilla, I. and Parham, P. and Shvartzshnaider, Y.},\n\tyear = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n \n Privacy governance not included: analysis of third parties in learning management systems.\n \n \n \n \n\n\n \n Sanfilippo, M. R.; Apthorpe, N.; Brehm, K.; and Shvartzshnaider, Y.\n\n\n \n\n\n\n Information and Learning Sciences, ahead-of-print(ahead-of-print). January 2023.\n \n\n\n\n
\n\n\n\n \n \n \"PrivacyPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{sanfilippo_privacy_2023,\n\ttitle = {Privacy governance not included: analysis of third parties in learning management systems},\n\tvolume = {ahead-of-print},\n\tissn = {2398-5348},\n\tshorttitle = {Privacy governance not included},\n\turl = {https://doi.org/10.1108/ILS-04-2023-0033},\n\tdoi = {10.1108/ILS-04-2023-0033},\n\tabstract = {Purpose This paper aims to address research gaps around third party data flows in education by investigating governance practices in higher education with respect to learning management system (LMS) ecosystems. The authors answer the following research questions: how are LMS and plugins/learning tools interoperability (LTI) governed at higher education institutions? Who is responsible for data governance activities around LMS? What is the current state of governance over LMS? What is the current state of governance over LMS plugins, LTI, etc.? What governance issues are unresolved in this domain? How are issues of privacy and governance regarding LMS and plugins/LTIs documented or communicated to the public and/or community members? Design/methodology/approach This study involved three components: (1) An online questionnaire about LMS, plugin and LTI governance practices from information technology professionals at seven universities in the USA (n = 4) and Canada (n = 3). The responses from these individuals helped us frame and design the interview schedule. (2) A review of public data from 112 universities about LMS plugin and LTI governance. Eighteen of these universities provide additional documentation, which we analyze in further depth. (3) A series of extensive interviews with 25 university data governance officers with responsibilities for LMS, plugin and/or LTI governance, representing 14 different universities. Findings The results indicate a portrait of fragmented and unobtrusive, unnoticed student information flows to third parties. From coordination problems on individual college campuses to disparate distributions of authority across campuses, as well as from significant data collection via individual LTIs to a shared problem of scope across many LTIs, the authors see that increased and intentional governance is needed to improve the state of student privacy and provide transparency in the complex environment around LMSs. Yet, the authors also see that there are logical paths forward based on successful governance and leveraging existing collaborative networks among data governance professionals in higher education. Originality/value Substantial prior work has examined issues of privacy in the education context, although little research has directly examined higher education institutions’ governance practices of LMS, plugin and LTI ecosystems. The tight integration of first and third-party tools in this ecosystem raises concerns that student data may be accessed and shared without sufficient transparency or oversight and in violation of established education privacy norms. However, these technologies and the university governance practices that could check inappropriate data handling remain under-scrutinized. This paper addresses this gap by investigating the governance practices of higher education institutions with respect to LMS ecosystems.},\n\tnumber = {ahead-of-print},\n\turldate = {2023-09-27},\n\tjournal = {Information and Learning Sciences},\n\tauthor = {Sanfilippo, Madelyn Rose and Apthorpe, Noah and Brehm, Karoline and Shvartzshnaider, Yan},\n\tmonth = jan,\n\tyear = {2023},\n\tkeywords = {Computing/technology policy, Educational technology, Empirical studies in social computing, Learning management systems, Privacy, Third-party data controllers},\n}\n\n
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\n\n\n
\n Purpose This paper aims to address research gaps around third party data flows in education by investigating governance practices in higher education with respect to learning management system (LMS) ecosystems. The authors answer the following research questions: how are LMS and plugins/learning tools interoperability (LTI) governed at higher education institutions? Who is responsible for data governance activities around LMS? What is the current state of governance over LMS? What is the current state of governance over LMS plugins, LTI, etc.? What governance issues are unresolved in this domain? How are issues of privacy and governance regarding LMS and plugins/LTIs documented or communicated to the public and/or community members? Design/methodology/approach This study involved three components: (1) An online questionnaire about LMS, plugin and LTI governance practices from information technology professionals at seven universities in the USA (n = 4) and Canada (n = 3). The responses from these individuals helped us frame and design the interview schedule. (2) A review of public data from 112 universities about LMS plugin and LTI governance. Eighteen of these universities provide additional documentation, which we analyze in further depth. (3) A series of extensive interviews with 25 university data governance officers with responsibilities for LMS, plugin and/or LTI governance, representing 14 different universities. Findings The results indicate a portrait of fragmented and unobtrusive, unnoticed student information flows to third parties. From coordination problems on individual college campuses to disparate distributions of authority across campuses, as well as from significant data collection via individual LTIs to a shared problem of scope across many LTIs, the authors see that increased and intentional governance is needed to improve the state of student privacy and provide transparency in the complex environment around LMSs. Yet, the authors also see that there are logical paths forward based on successful governance and leveraging existing collaborative networks among data governance professionals in higher education. Originality/value Substantial prior work has examined issues of privacy in the education context, although little research has directly examined higher education institutions’ governance practices of LMS, plugin and LTI ecosystems. The tight integration of first and third-party tools in this ecosystem raises concerns that student data may be accessed and shared without sufficient transparency or oversight and in violation of established education privacy norms. However, these technologies and the university governance practices that could check inappropriate data handling remain under-scrutinized. This paper addresses this gap by investigating the governance practices of higher education institutions with respect to LMS ecosystems.\n
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\n \n\n \n \n \n \n \n Technofuturism in Play.\n \n \n \n\n\n \n Sanfilippo, M. R.; and Shvartzshnaider, Y.\n\n\n \n\n\n\n In Governing Smart Cities as Knowledge Commons, pages 223. Cambridge University Press, 2023.\n \n\n\n\n
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@incollection{sanfilippo_technofuturism_2023,\n\ttitle = {Technofuturism in {Play}},\n\tbooktitle = {Governing {Smart} {Cities} as {Knowledge} {Commons}},\n\tpublisher = {Cambridge University Press},\n\tauthor = {Sanfilippo, Madelyn Rose and Shvartzshnaider, Yan},\n\tyear = {2023},\n\tpages = {223},\n}\n\n
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\n  \n 2022\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Stop the Spread: A Contextual Integrity Perspective on the Appropriateness of COVID-19 Vaccination Certificates.\n \n \n \n \n\n\n \n Zhang, S.; Shvartzshnaider, Y.; Feng, Y.; Nissenbaum, H.; and Sadeh, N.\n\n\n \n\n\n\n In 2022 ACM Conference on Fairness, Accountability, and Transparency, of FAccT '22, pages 1657–1670, New York, NY, USA, June 2022. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"StopPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{zhang_stop_2022,\n\taddress = {New York, NY, USA},\n\tseries = {{FAccT} '22},\n\ttitle = {Stop the {Spread}: {A} {Contextual} {Integrity} {Perspective} on the {Appropriateness} of {COVID}-19 {Vaccination} {Certificates}},\n\tisbn = {9781450393522},\n\tshorttitle = {Stop the {Spread}},\n\turl = {https://doi.org/10.1145/3531146.3533222},\n\tdoi = {10.1145/3531146.3533222},\n\tabstract = {We present an empirical study exploring how privacy influences the acceptance of vaccination certificate (VC) deployments across different realistic usage scenarios. The study employed the privacy framework of Contextual Integrity, which has been shown to be particularly effective in capturing people’s privacy expectations across different contexts. We use a vignette methodology, where we selectively manipulate salient contextual parameters to learn whether and how they affect people’s attitudes towards VCs. We surveyed 890 participants from a demographically-stratified sample of the US population to gauge the acceptance and overall attitudes towards possible VC deployments to enforce vaccination mandates and the different information flows VCs might entail. Analysis of results collected as part of this study is used to derive general normative observations about different possible VC practices and to provide guidance for the possible deployments of VCs in different contexts.},\n\turldate = {2022-06-21},\n\tbooktitle = {2022 {ACM} {Conference} on {Fairness}, {Accountability}, and {Transparency}},\n\tpublisher = {Association for Computing Machinery},\n\tauthor = {Zhang, Shikun and Shvartzshnaider, Yan and Feng, Yuanyuan and Nissenbaum, Helen and Sadeh, Norman},\n\tmonth = jun,\n\tyear = {2022},\n\tkeywords = {contextual integrity, information privacy, privacy norms, vaccination certificates},\n\tpages = {1657--1670},\n}\n\n
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\n We present an empirical study exploring how privacy influences the acceptance of vaccination certificate (VC) deployments across different realistic usage scenarios. The study employed the privacy framework of Contextual Integrity, which has been shown to be particularly effective in capturing people’s privacy expectations across different contexts. We use a vignette methodology, where we selectively manipulate salient contextual parameters to learn whether and how they affect people’s attitudes towards VCs. We surveyed 890 participants from a demographically-stratified sample of the US population to gauge the acceptance and overall attitudes towards possible VC deployments to enforce vaccination mandates and the different information flows VCs might entail. Analysis of results collected as part of this study is used to derive general normative observations about different possible VC practices and to provide guidance for the possible deployments of VCs in different contexts.\n
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\n  \n 2020\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Disaster privacy/privacy disaster.\n \n \n \n \n\n\n \n Sanfilippo, M. R.; Shvartzshnaider, Y.; Reyes, I.; Nissenbaum, H.; and Egelman, S.\n\n\n \n\n\n\n Journal of the Association for Information Science and Technology, 71(9): 1002–1014. September 2020.\n \n\n\n\n
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@article{sanfilippo_disaster_2020,\n\ttitle = {Disaster privacy/privacy disaster},\n\tvolume = {71},\n\tissn = {2330-1635, 2330-1643},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/asi.24353},\n\tdoi = {10.1002/asi.24353},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2022-04-11},\n\tjournal = {Journal of the Association for Information Science and Technology},\n\tauthor = {Sanfilippo, Madelyn R. and Shvartzshnaider, Yan and Reyes, Irwin and Nissenbaum, Helen and Egelman, Serge},\n\tmonth = sep,\n\tyear = {2020},\n\tkeywords = {publications},\n\tpages = {1002--1014},\n}\n\n
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\n  \n 2019\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Going against the (appropriate) flow: A contextual integrity approach to privacy policy analysis.\n \n \n \n \n\n\n \n Shvartzshnaider, Y.; Apthorpe, N.; Feamster, N.; and Nissenbaum, H.\n\n\n \n\n\n\n In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, volume 7, pages 162–170, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"GoingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{shvartzshnaider_going_2019,\n\ttitle = {Going against the (appropriate) flow: {A} contextual integrity approach to privacy policy analysis},\n\tvolume = {7},\n\turl = {https://nissenbaum.tech.cornell.edu/papers/Going%20Against%20the%20(Appropriate)%20Flow.pdf},\n\tbooktitle = {Proceedings of the {AAAI} {Conference} on {Human} {Computation} and {Crowdsourcing}},\n\tauthor = {Shvartzshnaider, Yan and Apthorpe, Noah and Feamster, Nick and Nissenbaum, Helen},\n\tyear = {2019},\n\tkeywords = {publications},\n\tpages = {162--170},\n}\n\n
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\n \n\n \n \n \n \n \n \n Vaccine: Using contextual integrity for data leakage detection.\n \n \n \n \n\n\n \n Shvartzshnaider, Y.; Pavlinovic, Z.; Balashankar, A.; Wies, T.; Subramanian, L.; Nissenbaum, H.; and Mittal, P.\n\n\n \n\n\n\n In The World Wide Web Conference, pages 1702–1712, 2019. \n \n\n\n\n
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@inproceedings{shvartzshnaider_vaccine_2019,\n\ttitle = {Vaccine: {Using} contextual integrity for data leakage detection},\n\turl = {https://dl.acm.org/doi/pdf/10.1145/3308558.3313655?casa_token=7wTqeNijuqMAAAAA:v8zQAREHXj68NGBEMz7QuZjVZFTu2QkDqP7isA8pYKwjBglRR_Wpoo34j2CsoFyq0tMWLd-tA7U9FVc},\n\tbooktitle = {The {World} {Wide} {Web} {Conference}},\n\tauthor = {Shvartzshnaider, Yan and Pavlinovic, Zvonimir and Balashankar, Ananth and Wies, Thomas and Subramanian, Lakshminarayanan and Nissenbaum, Helen and Mittal, Prateek},\n\tyear = {2019},\n\tkeywords = {publications},\n\tpages = {1702--1712},\n}\n
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\n  \n 2018\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Discovering smart home internet of things privacy norms using contextual integrity.\n \n \n \n \n\n\n \n Apthorpe, N.; Shvartzshnaider, Y.; Mathur, A.; Reisman, D.; and Feamster, N.\n\n\n \n\n\n\n Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(2): 1–23. 2018.\n Publisher: ACM New York, NY, USA\n\n\n\n
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@article{apthorpe_discovering_2018,\n\ttitle = {Discovering smart home internet of things privacy norms using contextual integrity},\n\tvolume = {2},\n\turl = {https://dl.acm.org/doi/pdf/10.1145/3214262},\n\tnumber = {2},\n\tjournal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},\n\tauthor = {Apthorpe, Noah and Shvartzshnaider, Yan and Mathur, Arunesh and Reisman, Dillon and Feamster, Nick},\n\tyear = {2018},\n\tnote = {Publisher: ACM New York, NY, USA},\n\tkeywords = {publications},\n\tpages = {1--23},\n}\n\n
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\n \n\n \n \n \n \n \n \n It Takes a Village: A Community Based Participatory Framework for Privacy Design.\n \n \n \n \n\n\n \n Mir, D. J; Shvartzshnaider, Y.; and Latonero, M.\n\n\n \n\n\n\n In 2018 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), pages 112–115, 2018. IEEE\n \n\n\n\n
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@inproceedings{mir_it_2018,\n\ttitle = {It {Takes} a {Village}: {A} {Community} {Based} {Participatory} {Framework} for {Privacy} {Design}},\n\turl = {https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8406569&casa_token=0eUDaIyeHgwAAAAA:alFqssV2228ZVh1yb6HneZ2FOx3nE-lbA5rsLbGHUBHs7ZembEDkM7rfHG7mT8myX5pmW-4ZCC0&tag=1},\n\tbooktitle = {2018 {IEEE} {European} {Symposium} on {Security} and {Privacy} {Workshops} ({EuroS}\\&{PW})},\n\tpublisher = {IEEE},\n\tauthor = {Mir, Darakhshan J and Shvartzshnaider, Yan and Latonero, Mark},\n\tyear = {2018},\n\tkeywords = {publications},\n\tpages = {112--115},\n}\n\n
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\n \n\n \n \n \n \n \n \n RECIPE: Applying Open Domain Question Answering to Privacy Policies.\n \n \n \n \n\n\n \n Shvartzshanider, Y.; Balashankar, A.; Wies, T.; and Subramanian, L.\n\n\n \n\n\n\n In Proceedings of the Workshop on Machine Reading for Question Answering, pages 71–77, Melbourne, Australia, 2018. Association for Computational Linguistics\n \n\n\n\n
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@inproceedings{shvartzshanider_recipe_2018,\n\taddress = {Melbourne, Australia},\n\ttitle = {{RECIPE}: {Applying} {Open} {Domain} {Question} {Answering} to {Privacy} {Policies}},\n\tshorttitle = {{RECIPE}},\n\turl = {http://aclweb.org/anthology/W18-2608},\n\tdoi = {10.18653/v1/W18-2608},\n\tlanguage = {en},\n\turldate = {2022-03-30},\n\tbooktitle = {Proceedings of the {Workshop} on {Machine} {Reading} for {Question} {Answering}},\n\tpublisher = {Association for Computational Linguistics},\n\tauthor = {Shvartzshanider, Yan and Balashankar, Ananth and Wies, Thomas and Subramanian, Lakshminarayanan},\n\tyear = {2018},\n\tkeywords = {publications},\n\tpages = {71--77},\n}\n\n
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\n  \n 2016\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Learning privacy expectations by crowdsourcing contextual informational norms.\n \n \n \n \n\n\n \n Shvartzshnaider, Y.; Tong, S.; Wies, T.; Kift, P.; Nissenbaum, H.; Subramanian, L.; and Mittal, P.\n\n\n \n\n\n\n In Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016. \n \n\n\n\n
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@inproceedings{shvartzshnaider_learning_2016,\n\ttitle = {Learning privacy expectations by crowdsourcing contextual informational norms},\n\turl = {https://privaci.info/papers/hcomp_paper.pdf},\n\tbooktitle = {Fourth {AAAI} {Conference} on {Human} {Computation} and {Crowdsourcing}},\n\tauthor = {Shvartzshnaider, Yan and Tong, Schrasing and Wies, Thomas and Kift, Paula and Nissenbaum, Helen and Subramanian, Lakshminarayanan and Mittal, Prateek},\n\tyear = {2016},\n\tkeywords = {publications},\n}\n\n
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