{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T19:02:36Z","timestamp":1773774156172,"version":"3.50.1"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319195803","type":"print"},{"value":"9783319195810","type":"electronic"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-19581-0_46","type":"book-chapter","created":{"date-parts":[[2015,6,4]],"date-time":"2015-06-04T02:30:20Z","timestamp":1433385020000},"page":"453-457","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["A Comparative Study on Twitter Sentiment Analysis: Which Features are Good?"],"prefix":"10.1007","author":[{"given":"Fajri","family":"Koto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mirna","family":"Adriani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,6,4]]},"reference":[{"key":"46_CR1","doi-asserted-by":"crossref","unstructured":"Bravo-Marquez, F., Mendoza, M., Poblete, B.: Combining strengths, emotions and polarities for boosting Twitter sentiment analysis. In: Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, vol.\u00a02 (2013)","DOI":"10.1145\/2502069.2502071"},{"key":"46_CR2","unstructured":"Raaijmakers, S., Kraaij, W.: A shallow approach to subjectivity classification. In: ICWSM (2008)"},{"key":"46_CR3","doi-asserted-by":"crossref","unstructured":"Aisopos, F., Papadakis, G., Tserpes, K., Varvarigou, T.: Content vs. context for sentiment analysis: a comparative analysis over microblogs. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, pp. 187\u2013196 (2012)","DOI":"10.1145\/2309996.2310028"},{"key":"46_CR4","unstructured":"Go, A., Bhayani, R., Huang, L.: Twitter sentiment classification using distant supervision. In: CS224N Project Report, Stanford (2009)"},{"key":"46_CR5","unstructured":"Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of twitter data. In: Proceedings of the Workshop on Languages in Social Media, pp. 30\u201338 (2011)"},{"key":"46_CR6","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 (2005)","DOI":"10.3115\/1220575.1220619"},{"key":"46_CR7","doi-asserted-by":"crossref","unstructured":"Liu, B., Hu, M., Cheng, J.: Opinion observer: analyzing and comparing opinions on the web. In: Proceedings of the 14th International Conference on World Wide Web, pp. 342\u2013351 (2005)","DOI":"10.1145\/1060745.1060797"},{"key":"46_CR8","unstructured":"Baccianella, S., Esuli, A., Sebastiani, F.: SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: LREC, vol. 10, pp. 2200\u20132204 (2010)"},{"key":"46_CR9","unstructured":"Bradley, M.M., Lang, P.J.: Affective norms for English words (ANEW): instruction manual and affective ratings. In: Technical report C-1, The Center for Research in Psychophysiology, University of Florida, pp. 1\u201345 (1999)"},{"key":"46_CR10","unstructured":"Nielsen, F.A.: A new ANEW: evaluation of a word list for sentiment analysis in microblogs. in: arXiv preprint arXiv: 1103.2903 (2011)"},{"issue":"3","key":"46_CR11","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 wordemotion association lexicon. Comput. Intell. 29(3), 436\u2013465 (2013)","journal-title":"Comput. Intell."},{"issue":"1","key":"46_CR12","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1002\/asi.21662","volume":"63","author":"M Thelwall","year":"2012","unstructured":"Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment strength detection for the social web. J. Am. Soc. Inf. Sci. Technol. 63(1), 163\u2013173 (2012)","journal-title":"J. Am. Soc. Inf. Sci. Technol."},{"issue":"3\u20134","key":"46_CR13","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1080\/02699939208411068","volume":"6","author":"P Ekman","year":"1992","unstructured":"Ekman, P.: An argument for basic emotions. Cogn. Emot. 6(3\u20134), 169\u2013200 (1992)","journal-title":"Cogn. Emot."},{"key":"46_CR14","volume-title":"The Psychology and Biology of Emotion","author":"R Plutchik","year":"1994","unstructured":"Plutchik, R.: The Psychology and Biology of Emotion. HarperCollins College Publishers, New York (1994)"},{"key":"46_CR15","unstructured":"Speriosu, M., Sudan, N., Upadhyay, S., Baldridge, J.: Twitter polarity classification with label propagation over lexical links and the follower graph. In: Proceedings of the First workshop on Unsupervised Learning in NLP, pp. 53\u201363 (2011)"},{"key":"46_CR16","doi-asserted-by":"crossref","unstructured":"Bird, S.: NLTK: the natural language toolkit. In: Proceedings of the COLING\/ACL on Interactive Presentation Sessions, pp. 69\u201372 (2006)","DOI":"10.3115\/1225403.1225421"}],"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\/978-3-319-19581-0_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T18:23:57Z","timestamp":1674239037000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-19581-0_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319195803","9783319195810"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-19581-0_46","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"4 June 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}