{"id":479,"date":"2016-10-19T19:36:46","date_gmt":"2016-10-20T00:36:46","guid":{"rendered":"http:\/\/wp.comminfo.rutgers.edu\/vsingh\/?page_id=479"},"modified":"2016-10-19T19:36:46","modified_gmt":"2016-10-20T00:36:46","slug":"cyberbullying-prevention","status":"publish","type":"page","link":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/cyberbullying-prevention\/","title":{"rendered":"Cyberbullying Prevention"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”3.22″ global_colors_info=”{}”][et_pb_row admin_label=”row” _builder_version=”3.25″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” use_border_color=”off” border_color=”#ffffff” border_style=”solid” global_colors_info=”{}”]<\/p>\n

Cyberbullying Prevention<\/strong><\/h1>\n

We utilize qualitative, quantitative, and computational approaches to counter cyberbullying. We have undertaken focus group interviews in school settings to understand cyberbullying [7], undertaken quantitative analysis to understand how social features relate with cyberbullying [3,9], and built predictive models to automatically detect cyberbullying [1-4, 6, 8-9]. Ours was one of the first efforts to use social features to predict cyberbullying [9]. In follow up work, we have understood how multimodal features are useful for cyberbullying detection [3, 6], how detection from multiple modalities can be probabilistically combined for cyberbullying detection [1, 8], how threads with cyberbullying evolve over time [4], and how cyberbullying detection algorithms can be made fairer [1,2].\u00a0\u00a0<\/p>\n

Related Publications <\/strong><\/p>\n

<\/span><\/p>\n

    \n
  1. Alasadi, J., Ramanathan, A., Atrey, P. &\u00a0<\/span>Singh, V. K.<\/strong>\u00a0<\/span>(2020).\u00a0<\/span>A Fairness-Aware Fusion Framework for Multimodal Cyberbullying Detection.\u00a0<\/a>In Proceedings of the IEEE International Conference on Multimedia Big Data.\u00a0<\/em><\/li>\n
  2. Singh, V.,<\/strong>\u00a0<\/span>& Hofenbitzer, C. (2019).\u00a0<\/span>Fairness across network positions in cyberbullying detection algorithms.<\/a>\u00a0<\/span>In\u00a02019 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)<\/em>\u00a0<\/span>(pp. 557-559). IEEE.<\/li>\n
  3. \u00a0Soni, D., &\u00a0<\/span>Singh, V. K.<\/em><\/strong>\u00a0(2018).\u00a0<\/span>See No Evil, Hear No Evil: Audio-Visual-Textual Cyberbullying Detection<\/a>.\u00a0Proceedings of the ACM on Human-Computer Interaction<\/em>, 2(CSCW), 164<\/span><\/li>\n
  4. Soni, D., & Singh, V. K.<\/strong>\u00a0(2018).<\/span>\u00a0Time Reveals All Wounds: Modeling Temporal Dynamics of Cyberbullying Sessions.<\/a>\u00a0In\u00a0<\/span>Proceedings of the Eleventh International AAAI Conference on Web and Social Media<\/em>\u00a0(pp. 684-687)<\/span><\/li>\n
  5. Huang, Q.,\u00a0<\/span>Singh, V. K.<\/em><\/strong>, & Atrey, P. K. (2018).\u00a0<\/span>On cyberbullying incidents and underlying online social relationships<\/a>.\u00a0Journal of Computational Social Science,<\/em>\u00a01(2), 241-260.\u00a0https:\/\/doi.org\/10.1007\/s42001-018-0026-9<\/a>.<\/span><\/li>\n
  6. Singh, V. K.,<\/strong>\u00a0<\/span>Ghosh, S., & Jose, C.\u00a0<\/span><\/sup>(2017).\u00a0<\/span>Toward multimodal cyberbullying detection.<\/a>\u00a0<\/span>In\u00a0Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems<\/em>\u00a0<\/span>(pp. 2090-2099). ACM.<\/li>\n
  7. Singh, V. K.,<\/strong>\u00a0<\/span>Radford, M. L., Huang, Q., & Furrer, S. (2017).\u00a0<\/span>They basically like destroyed the school one day: On Newer App Features and Cyberbullying in Schools.<\/a>\u00a0<\/span>In\u00a0Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing<\/em>\u00a0<\/span>(pp. 1210-1216). ACM<\/li>\n
  8. Singh, V. K.,<\/strong>\u00a0<\/span>Huang, Q., & Atrey, P. K. (2016).\u00a0<\/span>Cyberbullying detection using probabilistic socio-textual information fusion.<\/a>\u00a0<\/span>In\u00a0Proceedings of the 2016 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining<\/em>\u00a0<\/span>(pp. 884-887). IEEE Press.<\/li>\n
  9. Huang, Q.,\u00a0<\/span>Singh, V. K.,<\/strong>\u00a0& Atrey, P. K. (2014).\u00a0<\/span>Cyber bullying detection using social and textual analysis<\/a>. In\u00a0<\/span>Proceedings of the 3rd International Workshop on Socially-Aware Multimedia<\/em>\u00a0(pp. 3-6). ACM<\/span><\/li>\n<\/ol>\n

    Funding and Support<\/strong><\/p>\n

    We gratefully acknowledge the support from the National Science Foundation<\/a> for this project.
    We are also grateful to our collaborators at the     Rutgers Tyler Clementi Center <\/a>and the Graduate School of Applied and Professional Psychology<\/a>\u00a0for their continuing support of this project.<\/p>\n

    Datasets<\/strong><\/p>\n

    We are happy to share the cyberbullying labeled dataset with other interested researchers. We would ask you to sign an agreement respecting the privacy of the users in the dataset. Please email Vivek Singh (v.singh@rutgers.edu) to request the dataset.<\/p>\n

    [\/et_pb_text][et_pb_image src=”http:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-content\/uploads\/sites\/35\/2016\/10\/Slide3.jpg” align_tablet=”center” align_phone=”center” align_last_edited=”on|desktop” admin_label=”Image” _builder_version=”3.23″ use_border_color=”off” border_color=”#ffffff” border_style=”solid” animation=”off” sticky=”off” always_center_on_mobile=”on” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

    Cyberbullying Prevention We utilize qualitative, quantitative, and computational approaches to counter cyberbullying. We have undertaken focus group interviews in school settings to understand cyberbullying [7], undertaken quantitative analysis to understand […]<\/p>\n","protected":false},"author":2442,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"Cyberbullying Prevention<\/strong>\n\nWe are working on two projects related to cyberbullying prevention.\n

      \n \t
    1. Focus Group Studies to Understand Cyberbullying in Schools.<\/strong>\nThis exploratory work studies the effects of emerging app features on the cyberbullying practices in high school settings. These include the increasing prevalence of image\/video content, perceived ephemerality, anonymity, and hyperlocal communication. Based on qualitative analysis of focus groups and follow-up individual interviews with high school students, these features were found to influence the practice of cyberbullying, as well as creating negative socio-psychological effects. For example, visual data was found to be used in cyberbullying settings as evidence of contentious events, a repeated reminder, and caused a graphic impact on recipients. Similarly, perceived ephemerality of content was found to be associated with \u201cbroken expectations\u201d with respect to the apps and severe bullying outcomes for those affected. Results shed light on an important technology-mediated social phenomenon of cyberbullying, improve understanding of app use (and abuse) by the teenage user population, and pave the way for future research on countering app-centric cyberbullying.<\/li>\n \t
    2. Cyberbullying Detection Using Text and Social Network Analysis\u00a0<\/strong>\nThis project aims to define new approaches for automatic detection of cyberbullying by integrating the relevant research in social sciences and computer science. Cyberbullying is a critical social problem that occurs over a technical substrate. According to a recent National Crime Prevention Council report, more than 40% of teenagers in the US have reported being cyberbullied. This is especially worrying as the multiple studies have reported that the victims of cyberbullying often deal with psychiatric and psychosomatic disorders. Specifically, this research will advance the state of the art in cyberbullying detection beyond textual analysis by also giving due attention to the social relationships in which these bullying messages are exchanged. A higher accuracy at detection would allow for better mitigation of the cyberbullying phenomenon and may help improve the lives of thousands of victims who are cyberbullied each year. The results of this research will also open doors to employing social intervention mechanisms to help prevent cyberbullying incidents in future. The findings from this research will also validate and refine existing theories on cyberbullying and potentially advance the field by creating a wave of data-driven analysis of the phenomenon. The generated data set will be made available to the larger research community, thus enabling new findings that can help counter this social problem.<\/li>\n<\/ol>\nPublications\u00a0<\/strong>\n
        \n \t
      1. \n
      2. \n
        Qianjia Huang, Vivek Kumar Singh, and Pradeep Kumar Atrey. Cyberbullying detection using social network analysis. Submitted to: IEEE Transactions on Computational Social<\/div>\n
        Systems, 2016<\/div><\/li>\n \t
      3. \n
      4. \n
        Vivek Singh, Marie Radford, Huang Qianjia, and Susan Furrer. \u201cThey basically like destroyed the school one day\u201d: On newer app affordances and cyberbullying in schools<\/a>.<\/div>\n
        (To Appear:) Proceedings of the international conference on Computer-Supported Collaborative Work and Social Computing (CSCW). ACM, 2017.<\/div><\/li>\n<\/ol>\nFunding and Support<\/strong>\n\nWe gratefully acknowledge the support from the National Science Foundation<\/a> for this project.\nWe are also grateful to our collaborators at the Rutgers Tyler Clementi Center <\/a>and the Graduate School of Applied and Professional Psychology<\/a>\u00a0for their continuing support of this project.\n\nDatasets<\/strong>\n\nWe are happy to share the cyberbullying labeled dataset with other interested researchers. We would ask you to sign an agreement respecting the privacy of the users in the dataset. Please email Prof. Vivek Singh (v.singh@rutgers.edu) to request the dataset.\n\n ","_et_gb_content_width":"","footnotes":""},"class_list":["post-479","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/pages\/479","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/users\/2442"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/comments?post=479"}],"version-history":[{"count":0,"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/pages\/479\/revisions"}],"wp:attachment":[{"href":"https:\/\/sites.comminfo.rutgers.edu\/vsingh\/wp-json\/wp\/v2\/media?parent=479"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}