{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T17:03:35Z","timestamp":1770224615418,"version":"3.49.0"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030011284","type":"print"},{"value":"9783030011291","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01129-1_28","type":"book-chapter","created":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T03:26:43Z","timestamp":1537327603000},"page":"455-470","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Building and Validating Hierarchical Lexicons with a Case Study on Personal Values"],"prefix":"10.1007","author":[{"given":"Steven R.","family":"Wilson","sequence":"first","affiliation":[]},{"given":"Yiting","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Rada","family":"Mihalcea","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,20]]},"reference":[{"issue":"Jan","key":"28_CR1","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(Jan), 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Boyd, R.L., Wilson, S.R., Pennebaker, J.W., Kosinski, M., Stillwell, D.J., Mihalcea, R.: Values in words: using language to evaluate and understand personal values. In: ICWSM, pp. 31\u201340 (2015)","DOI":"10.1609\/icwsm.v9i1.14589"},{"key":"28_CR3","unstructured":"Chang, J., Gerrish, S., Wang, C., Boyd-Graber, J.L., Blei, D.M.: Reading tea leaves: how humans interpret topic models. In: Advances in Neural Information Processing Systems, pp. 288\u2013296 (2009)"},{"key":"28_CR4","volume-title":"Elements of Information Theory","author":"TM Cover","year":"2012","unstructured":"Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley, Hoboken (2012)"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Fast, E., Chen, B., Bernstein, M.S.: Empath: understanding topic signals in large-scale text. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 4647\u20134657. ACM (2016)","DOI":"10.1145\/2858036.2858535"},{"issue":"5","key":"28_CR6","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1037\/a0015141","volume":"96","author":"J Graham","year":"2009","unstructured":"Graham, J., Haidt, J., Nosek, B.A.: Liberals and conservatives rely on different sets of moral foundations. J. Pers. Soc. Psychol. 96(5), 1029 (2009)","journal-title":"J. Pers. Soc. Psychol."},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Igo, S.P., Riloff, E.: Corpus-based semantic lexicon induction with web-based corroboration. In: Proceedings of the Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics, pp. 18\u201326. Association for Computational Linguistics (2009)z","DOI":"10.3115\/1641968.1641971"},{"key":"28_CR8","unstructured":"Magnini, B., Cavaglia, G.: Integrating subject field codes into wordnet. In: LREC, pp. 1413\u20131418 (2000)"},{"issue":"3","key":"28_CR9","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1111\/j.1467-8640.2012.00460.x","volume":"29","author":"SM Mohammad","year":"2013","unstructured":"Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436\u2013465 (2013)","journal-title":"Comput. Intell."},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Morstatter, F., Liu, H.: A novel measure for coherence in statistical topic models. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Short Papers), vol. 2, pp. 543\u2013548 (2016)","DOI":"10.18653\/v1\/P16-2088"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Mrk\u0161i\u0107, N., S\u00e9aghdha, D.O., Thomson, B., Ga\u0161i\u0107, M., Rojas-Barahona, L., Su, P.H., Vandyke, D., Wen, T.H., Young, S.: Counter-fitting word vectors to linguistic constraints. arXiv preprint arXiv:1603.00892 (2016)","DOI":"10.18653\/v1\/N16-1018"},{"key":"28_CR12","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"28_CR13","unstructured":"Pennebaker, J.W., Boyd, R.L., Jordan, K., Blackburn, K.: The development and psychometric properties of liwc2015. Technical report (2015)"},{"key":"28_CR14","doi-asserted-by":"crossref","unstructured":"Rao, D., Ravichandran, D.: Semi-supervised polarity lexicon induction. In: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, pp. 675\u2013682. Association for Computational Linguistics (2009)","DOI":"10.3115\/1609067.1609142"},{"issue":"4","key":"28_CR15","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1002\/bs.3830070412","volume":"7","author":"PJ Stone","year":"1962","unstructured":"Stone, P.J., Bales, R.F., Namenwirth, J.Z., Ogilvie, D.M.: The general inquirer: a computer system for content analysis and retrieval based on the sentence as a unit of information. Syst. Res. Behav. Sci. 7(4), 484\u2013498 (1962)","journal-title":"Syst. Res. Behav. Sci."},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Thelen, M., Riloff, E.: A bootstrapping method for learning semantic lexicons using extraction pattern contexts. In: Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, vol. 10, pp. 214\u2013221. Association for Computational Linguistics (2002)","DOI":"10.3115\/1118693.1118721"},{"key":"28_CR17","unstructured":"Wieting, J., Bansal, M., Gimpel, K., Livescu, K.: Towards universal paraphrastic sentence embeddings. arXiv preprint arXiv:1511.08198 (2015)"},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing contextual polarity in phrase-level sentiment analysis. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 347\u2013354. Association for Computational Linguistics (2005)","DOI":"10.3115\/1220575.1220619"}],"container-title":["Lecture Notes in Computer Science","Social Informatics"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01129-1_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T06:30:52Z","timestamp":1693895452000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01129-1_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030011284","9783030011291"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01129-1_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"SocInfo","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Social Informatics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Saint-Petersburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Russia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socinfo2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/socinfo2018.hse.ru\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"110","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"30","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"32","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"27% - 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"}},{"value":"3,2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,54","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}