{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T12:35:27Z","timestamp":1761395727333,"version":"3.37.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030445836"},{"type":"electronic","value":"9783030445843"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-44584-3_6","type":"book-chapter","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T23:04:42Z","timestamp":1587510282000},"page":"67-79","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Towards Content Sensitivity Analysis"],"prefix":"10.1007","author":[{"given":"Elena","family":"Battaglia","sequence":"first","affiliation":[]},{"given":"Livio","family":"Bioglio","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5145-3438","authenticated-orcid":false,"given":"Ruggero G.","family":"Pensa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,22]]},"reference":[{"key":"6_CR1","doi-asserted-by":"publisher","first-page":"143631","DOI":"10.1109\/ACCESS.2019.2944723","volume":"7","author":"J Alemany","year":"2019","unstructured":"Alemany, J., del Val Noguera, E., Alberola, J.M., Garc\u00eda-Fornes, A.: Metrics for privacy assessment when sharing information in online social networks. IEEE Access 7, 143631\u2013143645 (2019)","journal-title":"IEEE Access"},{"key":"6_CR2","doi-asserted-by":"crossref","unstructured":"Biega, J.A., Gummadi, K.P., Mele, I., Milchevski, D., Tryfonopoulos, C., Weikum, G.: R-Susceptibility: an IR-centric approach to assessing privacy risks for users in online communities. In: Proceedings of ACM SIGIR 2016, pp. 365\u2013374 (2016)","DOI":"10.1145\/2911451.2911533"},{"key":"6_CR3","unstructured":"Celli, F., Pianesi, F., Stillwell, D., Kosinski, M.: Workshop on computational personality recognition: shared task. In: Proceedings of ICWSM 2013 (2013)"},{"key":"6_CR4","doi-asserted-by":"crossref","unstructured":"Clark, K., Manning, C.D.: Improving coreference resolution by learning entity-level distributed representations. In: Proceedings of ACL 2016 (2016)","DOI":"10.18653\/v1\/P16-1061"},{"key":"6_CR5","doi-asserted-by":"crossref","unstructured":"Correa, D., Silva, L.A., Mondal, M., Benevenuto, F., Gummadi, K.P.: The many shades of anonymity: characterizing anonymous social media content. In: Proceedings of ICWSM 2015, pp. 71\u201380 (2015)","DOI":"10.1609\/icwsm.v9i1.14635"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Gill, A.J., Vasalou, A., Papoutsi, C., Joinson, A.N.: Privacy dictionary: a linguistic taxonomy of privacy for content analysis. In: Proceedings of ACM CHI 2011, pp. 3227\u20133236 (2011)","DOI":"10.1145\/1978942.1979421"},{"key":"6_CR7","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/978-1-4614-3223-4_13","volume-title":"Mining Text Data","author":"B Liu","year":"2012","unstructured":"Liu, B., Zhang, L.: A survey of opinion mining and sentiment analysis. In: Aggarwal, C.C., Zhai, C. (eds.) Mining Text Data, pp. 415\u2013463. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-1-4614-3223-4_13"},{"key":"6_CR8","doi-asserted-by":"crossref","unstructured":"Liu, K., Terzi, E.: A framework for computing the privacy scores of users in online social networks. TKDD 5(1), 6:1\u20136:30 (2010)","DOI":"10.1145\/1870096.1870102"},{"issue":"4","key":"6_CR9","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1007\/s12559-018-9549-x","volume":"10","author":"Y Ma","year":"2018","unstructured":"Ma, Y., Peng, H., Khan, T., Cambria, E., Hussain, A.: Sentic LSTM: a hybrid network for targeted aspect-based sentiment analysis. Cogn. Comput. 10(4), 639\u2013650 (2018). https:\/\/doi.org\/10.1007\/s12559-018-9549-x","journal-title":"Cogn. Comput."},{"key":"6_CR10","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Proceedings of NIPS 2013, pp. 3111\u20133119 (2013)"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Oukemeni, S., Rif\u00e0-Pous, H., i Puig, J.M.M.: IPAM: information privacy assessment metric in microblogging online social networks. IEEE Access 7, 114817\u2013114836 (2019)","DOI":"10.1109\/ACCESS.2019.2932899"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Oukemeni, S., Rif\u00e0-Pous, H., i Puig, J.M.M.: Privacy analysis on microblogging online social networks: a survey. ACM Comput. Surv. 52(3), 60:1\u201360:36 (2019)","DOI":"10.1145\/3321481"},{"issue":"1\u20132","key":"6_CR13","first-page":"1","volume":"2","author":"B Pang","year":"2007","unstructured":"Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retrieval 2(1\u20132), 1\u2013135 (2007)","journal-title":"Found. Trends Inf. Retrieval"},{"key":"6_CR14","doi-asserted-by":"crossref","unstructured":"Peddinti, S.T., Korolova, A., Bursztein, E., Sampemane, G.: Cloak and swagger: understanding data sensitivity through the lens of user anonymity. In: Proceedings of IEEE SP 2014, pp. 493\u2013508 (2014)","DOI":"10.1109\/SP.2014.38"},{"key":"6_CR15","doi-asserted-by":"crossref","unstructured":"Peddinti, S.T., Ross, K.W., Cappos, J.: Finding sensitive accounts on Twitter: an automated approach based on follower anonymity. In: Proceedings of ICWSM 2016, pp. 655\u2013658 (2016)","DOI":"10.1609\/icwsm.v10i1.14782"},{"issue":"3","key":"6_CR16","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/MSP.2017.74","volume":"15","author":"ST Peddinti","year":"2017","unstructured":"Peddinti, S.T., Ross, K.W., Cappos, J.: User anonymity on Twitter. IEEE Secur. Privacy 15(3), 84\u201387 (2017)","journal-title":"IEEE Secur. Privacy"},{"key":"6_CR17","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. In: Proceedings of EMNLP 2014, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"6_CR18","doi-asserted-by":"crossref","unstructured":"Pensa, R.G., di Blasi, G., Bioglio, L.: Network-aware privacy risk estimation in online social networks. Soc. Netw. Analys. Mining 9(1), 15:1\u201315:15 (2019)","DOI":"10.1007\/s13278-019-0558-x"},{"key":"6_CR19","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.eswa.2017.05.054","volume":"86","author":"RG Pensa","year":"2017","unstructured":"Pensa, R.G., Blasi, G.D.: A privacy self-assessment framework for online social networks. Expert Syst. Appl. 86, 18\u201331 (2017)","journal-title":"Expert Syst. Appl."},{"issue":"6","key":"6_CR20","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/MIS.2018.2882362","volume":"33","author":"S Poria","year":"2018","unstructured":"Poria, S., Majumder, N., Hazarika, D., Cambria, E., Gelbukh, A.F., Hussain, A.: Multimodal sentiment analysis: addressing key issues and setting up the baselines. IEEE Intell. Syst. 33(6), 17\u201325 (2018)","journal-title":"IEEE Intell. Syst."},{"key":"6_CR21","unstructured":"Surdeanu, M., McClosky, D., Smith, M., Gusev, A., Manning, C.D.: Customizing an information extraction system to a new domain. In: Proceedings of RELMS@ACL 2011, pp. 2\u201310 (2011)"},{"issue":"11","key":"6_CR22","doi-asserted-by":"publisher","first-page":"2095","DOI":"10.1002\/asi.21610","volume":"62","author":"A Vasalou","year":"2011","unstructured":"Vasalou, A., Gill, A.J., Mazanderani, F., Papoutsi, C., Joinson, A.N.: Privacy dictionary: a new resource for the automated content analysis of privacy. JASIST 62(11), 2095\u20132105 (2011)","journal-title":"JASIST"},{"key":"6_CR23","doi-asserted-by":"crossref","unstructured":"Wagner, I., Eckhoff, D.: Technical privacy metrics: a systematic survey. ACM Comput. Surv. 51(3), 57:1\u201357:38 (2018)","DOI":"10.1145\/3168389"},{"issue":"5","key":"6_CR24","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1109\/TIFS.2017.2787986","volume":"13","author":"J Yu","year":"2018","unstructured":"Yu, J., Kuang, Z., Zhang, B., Zhang, W., Lin, D., Fan, J.: Leveraging content sensitiveness and user trustworthiness to recommend fine-grained privacy settings for social image sharing. IEEE Trans. Inf. Forensics Secur. 13(5), 1317\u20131332 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"5","key":"6_CR25","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1109\/TIFS.2016.2636090","volume":"12","author":"J Yu","year":"2017","unstructured":"Yu, J., Zhang, B., Kuang, Z., Lin, D., Fan, J.: iPrivacy: image privacy protection by identifying sensitive objects via deep multi-task learning. IEEE Trans. Inf. Forensics Secur. 12(5), 1005\u20131016 (2017)","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XVIII"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-44584-3_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T05:34:43Z","timestamp":1696052083000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-44584-3_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030445836","9783030445843"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-44584-3_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Konstanz","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 April 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 April 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ida2020.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"114","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}