Do My Emotions Influence What I Share? Analysing the Effects of Emotions on Privacy Leakage in Twitter

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dc.contributor.author Mittal, Manasi
dc.contributor.author Asghar, Muhammad Rizwan
dc.contributor.author Tripathi, Arvind
dc.contributor.editor Wang, GJ
dc.contributor.editor Ko, R
dc.contributor.editor Bhuiyan, MZA
dc.contributor.editor Pan, Y
dc.coverage.spatial Guangzhou, PEOPLES R CHINA
dc.date.accessioned 2021-12-06T02:25:10Z
dc.date.available 2021-12-06T02:25:10Z
dc.date.issued 2021-1-1
dc.identifier.citation 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2020, pp. 1228-1235
dc.identifier.isbn 9781665403924
dc.identifier.issn 2324-898X
dc.identifier.uri https://hdl.handle.net/2292/57643
dc.description.abstract Social media has become an integral part of modernday society. With increasingly digital societies, individuals have become more familiar and comfortable in using Online Social Networks (OSNs) for just about every aspect of their lives. This higher level of comfort leads to users spilling their emotions on OSNs and eventually their private information. In this work, we aim to investigate the relationship between users' emotions and private information in their tweets. Our research question is whether users' emotions, expressed in their tweets, affect their likelihood to reveal their own private information (privacy leakage) in subsequent tweets. In contrast to existing survey-based approaches, we use an inductive, data-driven approach to answer our research question. We use state-of-the-art techniques to classify users' emotions, and privacy scoring and employ a new technique involving BERT for binary detection of sensitive data. We use two parallel classification frameworks: one that takes the user's emotional state into account and the other for the detection of sensitive data in tweets. Consecutively, we identify individual cases of correlation between the two. We bring the two classifiers together to interpret the changes in both factors over time during a conversation between individuals. Variations were found with respect to the kinds of private information revealed in different states. Our results show that being in negative emotional states, such as sadness, anger or fear, leads to higher privacy leakage than otherwise.
dc.publisher IEEE
dc.relation.ispartof 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
dc.relation.ispartofseries 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.rights.uri https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/#accepted
dc.subject Science & Technology
dc.subject Technology
dc.subject Computer Science, Hardware & Architecture
dc.subject Computer Science, Information Systems
dc.subject Computer Science, Theory & Methods
dc.subject Telecommunications
dc.subject Computer Science
dc.subject Privacy
dc.subject Emotions
dc.subject Twitter
dc.title Do My Emotions Influence What I Share? Analysing the Effects of Emotions on Privacy Leakage in Twitter
dc.type Conference Item
dc.identifier.doi 10.1109/trustcom50675.2020.00165
pubs.begin-page 1228
pubs.volume 00
dc.date.updated 2021-11-13T21:17:11Z
dc.rights.holder Copyright: IEEE en
pubs.author-url http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000671077600151&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e41486220adb198d0efde5a3b153e7d
pubs.end-page 1235
pubs.finish-date 2021-1-1
pubs.publication-status Published
pubs.start-date 2020-12-29
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.elements-id 842636


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