{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T04:02:15Z","timestamp":1751256135231,"version":"3.41.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319729251"},{"type":"electronic","value":"9783319729268"}],"license":[{"start":{"date-parts":[[2017,12,21]],"date-time":"2017-12-21T00:00:00Z","timestamp":1513814400000},"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\/978-3-319-72926-8_13","type":"book-chapter","created":{"date-parts":[[2017,12,20]],"date-time":"2017-12-20T17:42:36Z","timestamp":1513791756000},"page":"146-157","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter"],"prefix":"10.1007","author":[{"given":"Stefano","family":"Cagnoni","sequence":"first","affiliation":[]},{"given":"Paolo","family":"Fornacciari","sequence":"additional","affiliation":[]},{"given":"Juxhino","family":"Kavaja","sequence":"additional","affiliation":[]},{"given":"Monica","family":"Mordonini","sequence":"additional","affiliation":[]},{"given":"Agostino","family":"Poggi","sequence":"additional","affiliation":[]},{"given":"Alex","family":"Solimeo","sequence":"additional","affiliation":[]},{"given":"Michele","family":"Tomaiuolo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,12,21]]},"reference":[{"key":"13_CR1","unstructured":"Yan, J.L.S., Turtle, H.R., Liddy, E.D.: EmoTweet-28: a fine-grained emotion corpus for sentiment analysis. In: Proceedings of the 10th International Conference on Language Resources and Evaluation. LREC 2016, pp. 1149\u20131156 (2016)"},{"key":"13_CR2","doi-asserted-by":"publisher","first-page":"18","DOI":"10.4018\/IJISMD.2016010102","volume":"7","author":"E Franchi","year":"2016","unstructured":"Franchi, E., Poggi, A., Tomaiuolo, M.: Social media for online collaboration in firms and organizations. Int. J. Inf. Syst. Model. Des. (IJISMD) 7, 18\u201331 (2016)","journal-title":"Int. J. Inf. Syst. Model. Des. (IJISMD)"},{"key":"13_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/978-3-319-49130-1_4","volume-title":"AI*IA 2016 Advances in Artificial Intelligence","author":"L Sani","year":"2016","unstructured":"Sani, L., et al.: Efficient search of relevant structures in complex systems. In: Adorni, G., Cagnoni, S., Gori, M., Maratea, M. (eds.) AI*IA 2016. LNCS (LNAI), vol. 10037, pp. 35\u201348. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49130-1_4"},{"key":"13_CR4","unstructured":"Amoretti, M., Ferrari, A., Fornacciari, P., Mordonini, M., Rosi, F., Tomaiuolo, M.: Local-first algorithms for community detection. In: 2nd International Workshop on Knowledge Discovery on the WEB, KDWeb 2016 (2016)"},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00500-016-2449-7","volume":"21","author":"P Ducange","year":"2017","unstructured":"Ducange, P., Pecori, R., Mezzina, P.: A glimpse on big data analytics in the framework of marketing strategies. Soft. Comput. 21, 1\u201318 (2017)","journal-title":"Soft. Comput."},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Bollen, J., Mao, H., Pepe, A.: Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. In: ICWSM, vol. 11, pp. 450\u2013453 (2011)","DOI":"10.1609\/icwsm.v5i1.14171"},{"key":"13_CR7","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s12652-011-0065-z","volume":"4","author":"R Ugolotti","year":"2013","unstructured":"Ugolotti, R., Sassi, F., Mordonini, M., Cagnoni, S.: Multi-sensor system for detection and classification of human activities. J. Ambient Intell. Humaniz. Comput. 4, 27\u201341 (2013)","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Matrella, G., Parada, G., Mordonini, M., Cagnoni, S.: A video-based fall detector sensor well suited for a data-fusion approach. In: Assistive Technology from Adapted Equipment to Inclusive Environments. Assistive Technology Research Series, vol. 25, pp. 327\u2013331 (2009)","DOI":"10.3233\/978-1-60750-042-1-327"},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00416ED1V01Y201204HLT016","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5, 1\u2013167 (2012)","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Mohammad, S.M.: Sentiment analysis: detecting valence, emotions, and other affectual states from text. In: Emotion Measurement (2015)","DOI":"10.1016\/B978-0-08-100508-8.00009-6"},{"key":"13_CR11","unstructured":"Fornacciari, P., Mordonini, M., Tomauiolo, M.: Social network and sentiment analysis on Twitter: towards a combined approach. In: 1st International Workshop on Knowledge Discovery on the WEB, KDWeb 2015 (2015)"},{"key":"13_CR12","unstructured":"Mislove, A., Lehmann, S., Ahn, Y.Y., Onnela, J.P., Rosenquist, J.N.: Pulse of the nation: US mood throughout the day inferred from twitter. Northeastern University (2010)"},{"key":"13_CR13","unstructured":"Allisio, L., Mussa, V., Bosco, C., Patti, V., Ruffo, G.: Felicitt\u00e0: Visualizing and estimating happiness in italian cities from geotagged tweets. In: ESSEM@ AI* IA, pp. 95\u2013106 (2013)"},{"key":"13_CR14","unstructured":"Healey, C., Ramaswamy, S.: Visualizing Twitter sentiment (2010). Accessed 17 Jun 2016"},{"key":"13_CR15","unstructured":"Strapparava, C., Valitutti, A., et al.: Wordnet affect: an affective extension of wordnet. In: LREC, vol. 4, pp. 1083\u20131086 (2004)"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Strapparava, C., Mihalcea, R.: Learning to identify emotions in text. In: Proceedings of the 2008 ACM symposium on Applied computing, pp. 1556\u20131560. ACM (2008)","DOI":"10.1145\/1363686.1364052"},{"key":"13_CR17","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.knosys.2014.05.005","volume":"69","author":"S Poria","year":"2014","unstructured":"Poria, S., Cambria, E., Winterstein, G., Huang, G.B.: Sentic patterns: dependency-based rules for concept-level sentiment analysis. Knowl. Based Syst. 69, 45\u201363 (2014)","journal-title":"Knowl. Based Syst."},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Kao, E.C., Liu, C.C., Yang, T.H., Hsieh, C.T., Soo, V.W.: Towards text-based emotion detection a survey and possible improvements. In: 2009 International Conference on Information Management and Engineering, ICIME 2009, pp. 70\u201374. IEEE (2009)","DOI":"10.1109\/ICIME.2009.113"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Al-Hajjar, D., Syed, A.Z.: Applying sentiment and emotion analysis on brand tweets for digital marketing. In: 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp. 1\u20136. IEEE (2015)","DOI":"10.1109\/AEECT.2015.7360592"},{"key":"13_CR20","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":"13_CR21","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/coin.12024","volume":"31","author":"SM Mohammad","year":"2015","unstructured":"Mohammad, S.M., Kiritchenko, S.: Using hashtags to capture fine emotion categories from tweets. Comput. Intell. 31, 301\u2013326 (2015)","journal-title":"Comput. Intell."},{"key":"13_CR22","unstructured":"Ghazi, D., Inkpen, D., Szpakowicz, S.: Hierarchical versus flat classification of emotions in text. In: Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pp. 140\u2013146. Association for Computational Linguistics (2010)"},{"key":"13_CR23","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/978-3-319-49130-1_5","volume-title":"AI*IA 2016 Advances in Artificial Intelligence","author":"G Angiani","year":"2016","unstructured":"Angiani, G., Cagnoni, S., Chuzhikova, N., Fornacciari, P., Mordonini, M., Tomaiuolo, M.: Flat and hierarchical classifiers for detecting emotion in tweets. In: Adorni, G., Cagnoni, S., Gori, M., Maratea, M. (eds.) AI*IA 2016. LNCS (LNAI), vol. 10037, pp. 51\u201364. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49130-1_5"},{"key":"13_CR24","volume-title":"Emotions in Social Psychology: Essential Readings","author":"WG Parrott","year":"2001","unstructured":"Parrott, W.G.: Emotions in Social Psychology: Essential Readings. Psychology Press, Philadelphia (2001)"},{"key":"13_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1007\/978-3-642-37256-8_11","volume-title":"Computational Linguistics and Intelligent Text Processing","author":"J Suttles","year":"2013","unstructured":"Suttles, J., Ide, N.: Distant supervision for emotion classification with discrete binary values. In: Gelbukh, A. (ed.) CICLing 2013, Part II. LNCS, vol. 7817, pp. 121\u2013136. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-37256-8_11"},{"key":"13_CR26","volume-title":"Emotion: Theory, Research and Experience","author":"R Plutchik","year":"1986","unstructured":"Plutchik, R., Kellerman, H.: Emotion: Theory, Research and Experience. Academic press, New York (1986)"},{"key":"13_CR27","unstructured":"Go, A., Bhayani, R., Huang, L.: Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford 1 (2009)"},{"key":"13_CR28","unstructured":"Purver, M., Battersby, S.: Experimenting with distant supervision for emotion classification. In: Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, pp. 482\u2013491. Association for Computational Linguistics (2012)"},{"key":"13_CR29","first-page":"41","volume":"51","author":"A Intxaurrondo","year":"2013","unstructured":"Intxaurrondo, A., Surdeanu, M., De Lacalle, O.L., Agirre, E.: Removing noisy mentions for distant supervision. Procesamiento del lenguaje natural 51, 41\u201348 (2013)","journal-title":"Procesamiento del lenguaje natural"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"Roth, B., Barth, T., Wiegand, M., Klakow, D.: A survey of noise reduction methods for distant supervision. In: Proceedings of the 2013 Workshop on Automated Knowledge Base Construction, pp. 73\u201378. ACM (2013)","DOI":"10.1145\/2509558.2509571"},{"key":"13_CR31","unstructured":"Nakov, P., Kozareva, Z., Ritter, A., Rosenthal, S., Stoyanov, V., Wilson, T.: Semeval-2013 task 2: Sentiment analysis in twitter (2013)"},{"key":"13_CR32","unstructured":"Mohammad, S.M.: # Emotional tweets. In: Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the Main Conference and the Shared Task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation. SemEval 2012, pp. 246\u2013255. Association for Computational Linguistics, Stroudsburg (2012)"}],"container-title":["Lecture Notes in Computer Science","Machine Learning, Optimization, and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-72926-8_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T03:08:11Z","timestamp":1751166491000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-72926-8_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,21]]},"ISBN":["9783319729251","9783319729268"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-72926-8_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017,12,21]]},"assertion":[{"value":"21 December 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MOD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Machine Learning, Optimization, and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Volterra","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mod2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.taosciences.it\/mod\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}