{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T11:51:44Z","timestamp":1777204304587,"version":"3.51.4"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031084720","type":"print"},{"value":"9783031084737","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08473-7_33","type":"book-chapter","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T18:03:10Z","timestamp":1655402590000},"page":"358-369","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Detecting Early Signs of\u00a0Depression in\u00a0the\u00a0Conversational Domain: The Role of\u00a0Transfer Learning in\u00a0Low-Resource Scenarios"],"prefix":"10.1007","author":[{"given":"Petr","family":"Lorenc","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana-Sabina","family":"Uban","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Rosso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"\u0160ediv\u00fd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,13]]},"reference":[{"key":"33_CR1","unstructured":"Abed-Esfahani, P., et al.: Transfer learning for depression: early detection and severity prediction from social media postings. In: CLEF (Working Notes), vol. 1, pp. 1\u20136 (2019)"},{"key":"33_CR2","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association: Diagnostic and statistical manual of mental disorders, 5th edn. Autor, Washington, DC (2013)","DOI":"10.1176\/appi.books.9780890425596"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Batista, G., Prati, R., Monard, M.C.: A study of the behavior of several methods for balancing machine learning training data. In: SIGKDD Explorations, vol. 6, pp. 20\u201329 (2004)","DOI":"10.1145\/1007730.1007735"},{"key":"33_CR4","doi-asserted-by":"crossref","unstructured":"Cer, D.M., et al.: Universal sentence encoder. arXiv (2018)","DOI":"10.18653\/v1\/D18-2029"},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Coppersmith, G., Dredze, M., Harman, C., Hollingshead, K., Mitchell, M.: CLPsych 2015 shared task: Depression and PTSD on Twitter. In: Proceedings of the 2nd CLPsych, Denver, Colorado, 5 June 2015, pp. 31\u201339. ACL (2015)","DOI":"10.3115\/v1\/W15-1204"},{"key":"33_CR6","unstructured":"DeVault, D., et al.: Verbal indicators of psychological distress in interactive dialogue with a virtual human. In: SIGDIAL 2013 Conference, pp. 193\u2013202. Association for Computational Linguistics (2013)"},{"key":"33_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. In: NAACL (2019)"},{"key":"33_CR8","unstructured":"Dinkel, H., Wu, M., Yu, K.: Text-based depression detection: what triggers an alert. arXiv (2019)"},{"key":"33_CR9","doi-asserted-by":"crossref","unstructured":"Finch, S.E., et al.: Emora: an inquisitive social chatbot who cares for you. In: Alexa Prize Proceedings, vol. 3 (2020)","DOI":"10.2307\/j.ctv15wxnsd.6"},{"key":"33_CR10","unstructured":"Gabriel, R., et al.: Further advances in open domain dialog systems in the third Alexa prize socialbot grand challenge. In: Alexa Prize Proceedings, vol. 3 (2020)"},{"key":"33_CR11","unstructured":"Gratch, J., et al.: The distress analysis interview corpus of human and computer interviews. In: LREC 2014, pp. 3123\u20133128 (2014)"},{"key":"33_CR12","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9, 1735\u201380 (1997)","journal-title":"Neural Comput."},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Islam, M.R., Kabir, A., Ahmed, A., Kamal, A., Wang, H., Ulhaq, A.: Depression detection from social network data using machine learning techniques. In: Health Information Science and Systems, vol. 6, p. 8 (2018)","DOI":"10.1007\/s13755-018-0046-0"},{"key":"33_CR14","doi-asserted-by":"crossref","unstructured":"Lee, M., Ackermans, S., van As, N., Chang, H., Lucas, E., IJsselsteijn, W.: Caring for Vincent: a chatbot for self-compassion. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (2019)","DOI":"10.1145\/3290605.3300932"},{"key":"33_CR15","doi-asserted-by":"crossref","unstructured":"Liu, N.F., Gardner, M., Belinkov, Y., Peters, M.E., Smith, N.A.: Linguistic knowledge and transferability of contextual representations. In: NAACL-HLT (2019)","DOI":"10.18653\/v1\/N19-1112"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Losada, D.E., Crestani, F.: A test collection for research on depression and language use. In: Conference Labs of the Evaluation Forum (2016)","DOI":"10.1007\/978-3-319-44564-9_3"},{"key":"33_CR17","doi-asserted-by":"crossref","unstructured":"Mallol-Ragolta, A., Zhao, Z., Stappen, L., Cummins, N., Schuller, B.: A hierarchical attention network-based approach for depression detection from transcribed clinical interviews. In: Interspeech, pp. 221\u2013225 (2019)","DOI":"10.21437\/Interspeech.2019-2036"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"McCloskey, M., Cohen, N.J.: Catastrophic interference in connectionist networks: the sequential learning problem. In: Psychology of Learning and Motivation, vol. 24, pp. 109\u2013165 (1989)","DOI":"10.1016\/S0079-7421(08)60536-8"},{"key":"33_CR19","doi-asserted-by":"crossref","unstructured":"Mohammad, S., Turney, P.: Crowdsourcing a word-emotion association lexicon. In: Computational Intelligence, vol. 29 (2013)","DOI":"10.1111\/j.1467-8640.2012.00460.x"},{"key":"33_CR20","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1080\/00220670209598786","volume":"96","author":"J Peng","year":"2002","unstructured":"Peng, J., Lee, K., Ingersoll, G.: An introduction to logistic regression analysis and reporting. J. Educ. Res. 96, 3\u201314 (2002)","journal-title":"J. Educ. Res."},{"key":"33_CR21","unstructured":"Pennebaker, J.W., Francis, M.E., Booth, R.J.: Linguistic Inquiry and Word Count, vol. 71. Lawrence Erlbaum Associates (2001)"},{"key":"33_CR22","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: EMNLP, vol. 14, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"33_CR23","unstructured":"Phang, J., F\u00e9vry, T., Bowman, S.R.: Sentence encoders on stilts: supplementary training on intermediate labeled-data tasks. arXiv (2018)"},{"key":"33_CR24","unstructured":"Pichl, J., Marek, P., Konr\u00e1d, J., Lorenc, P., Ta, V.D., Sediv\u00fd, J.: Alquist 3.0: Alexa prize bot using conversational knowledge graph. In: Alexa Prize Proceedings, vol. 3 (2020)"},{"key":"33_CR25","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using siamese BERT-networks. In: Association for Computational Linguistics (EMNLP), November 2019 (2019). https:\/\/arxiv.org\/abs\/1908.10084","DOI":"10.18653\/v1\/D19-1410"},{"key":"33_CR26","doi-asserted-by":"crossref","unstructured":"Rutowski, T., Shriberg, E., Harati, A., Lu, Y., Chlebek, P., Oliveira, R.: Depression and anxiety prediction using deep language models and transfer learning. In: 7th BESC, vol. 1, pp. 1\u20136 (2020)","DOI":"10.1109\/BESC51023.2020.9348290"},{"key":"33_CR27","unstructured":"Snoek, J., Larochelle, H., Adams, R.P.: Practical Bayesian optimization of machine learning algorithms. In: Advances in Neural Information Processing Systems, vol. 25. Curran Associates, Inc. (2012)"},{"key":"33_CR28","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1177\/2050157917708329","volume":"5","author":"E Tsetsi","year":"2017","unstructured":"Tsetsi, E., Rains, S.: Smartphone internet access and use: extending the digital divide and usage gap. Mob. Media Commun. 5, 239\u2013255 (2017)","journal-title":"Mob. Media Commun."},{"key":"33_CR29","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1016\/j.future.2021.05.032","volume":"124","author":"AS Uban","year":"2021","unstructured":"Uban, A.S., Chulvi, B., Rosso, P.: An emotion and cognitive based analysis of mental health disorders from social media data. Fut. Gener. Comput. Syst. 124, 480\u2013494 (2021)","journal-title":"Fut. Gener. Comput. Syst."},{"key":"33_CR30","unstructured":"Uban, A.S., Chulvi, B., Rosso, P.: Multi-aspect transfer learning for detecting low resource mental disorders on social media. In: Proceedings of the 13th Language Resources and Evaluation Conference (2022, to appear)"},{"key":"33_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"KR Weiss","year":"2016","unstructured":"Weiss, K.R., Khoshgoftaar, T., Wang, D.: A survey of transfer learning. J. Big Data 3, 1\u201340 (2016)","journal-title":"J. Big Data"},{"key":"33_CR32","unstructured":"Wolohan, J., Hiraga, M., Mukherjee, A., Sayyed, Z.A., Millard, M.: Detecting linguistic traces of depression in topic-restricted text: attending to self-stigmatized depression with NLP. In: Language Cognition and Computational Models, Santa Fe, New Mexico, USA, August 2018, pp. 11\u201321. ACL (2018)"},{"key":"33_CR33","doi-asserted-by":"crossref","unstructured":"Xezonaki, D., Paraskevopoulos, G., Potamianos, A., Narayanan, S.: Affective conditioning on hierarchical attention networks applied to depression detection from transcribed clinical interviews. In: Interspeech, pp. 4556\u20134560. ISCA (2020)","DOI":"10.21437\/Interspeech.2020-2819"},{"key":"33_CR34","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of the 2016 (NAACL-HLT), pp. 1480\u20131489 (2016)","DOI":"10.18653\/v1\/N16-1174"},{"key":"33_CR35","doi-asserted-by":"crossref","unstructured":"Yates, A., Cohan, A., Goharian, N.: Depression and self-harm risk assessment in online forums. In: EMNLP, Copenhagen, Denmark, September 2017, pp. 2968\u20132978. ACL (2017)","DOI":"10.18653\/v1\/D17-1322"},{"key":"33_CR36","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s13042-010-0001-0","volume":"1","author":"Y Zhang","year":"2010","unstructured":"Zhang, Y., Jin, R., Zhou, Z.H.: Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. 1, 43\u201352 (2010)","journal-title":"Int. J. Mach. Learn. Cybern."}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08473-7_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T08:44:22Z","timestamp":1700729062000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08473-7_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031084720","9783031084737"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08473-7_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"13 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Valencia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/nldb2022.prhlt.upv.es\/","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 (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":"106","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":"28","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":"20","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":"26% - 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","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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}