{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:46:24Z","timestamp":1775144784391,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":31,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1145\/2948992.2949022","type":"proceedings-article","created":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T15:17:25Z","timestamp":1469459845000},"page":"44-50","source":"Crossref","is-referenced-by-count":12,"title":["Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams"],"prefix":"10.1145","author":[{"given":"Pedro","family":"Saleiro","sequence":"first","affiliation":[{"name":"DEI-FEUP, LIACC, University of Porto, Porto, Portugal"}]},{"given":"Lu\u00eds","family":"Gomes","sequence":"additional","affiliation":[{"name":"DEI-FEUP, University of Porto, Porto, Portugal"}]},{"given":"Carlos","family":"Soares","sequence":"additional","affiliation":[{"name":"DEI-FEUP, INESC-TEC, University of Porto, Porto, Portugal"}]}],"member":"320","reference":[{"key":"key-10.1145\/2948992.2949022-1","unstructured":"C. Johnson, P. Shukla, and S. Shukla. On classifying the political sentiment of tweets. 2012."},{"key":"key-10.1145\/2948992.2949022-2","doi-asserted-by":"crossref","unstructured":"B. Connor, R. Balasubramanyan, B. Routledge, and N. Smith. From tweets to polls: Linking text sentiment to public opinion time series. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, pages 122--129, May 2010.","DOI":"10.1609\/icwsm.v4i1.14031"},{"key":"key-10.1145\/2948992.2949022-3","unstructured":"A. Kohut, S. Keeter, C. Doherty, M. Dimock, A. Directors, and L. Christian. Assessing the representativeness of public opinion surveys. 2012."},{"key":"key-10.1145\/2948992.2949022-4","unstructured":"A. Bermingham and A. Smeaton. On using twitter to monitor political sentiment and predict election results. Workshop at the International Joint Conference for Natural Language Processing (IJCNLP), November 2011."},{"key":"key-10.1145\/2948992.2949022-5","unstructured":"Pedro Saleiro, Jorge Teixeira, Carlos Soares, and Eugénio Oliveira. Timemachine: Entity-centric search and visualization of news archives. In Advances in Information Retrieval: 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings, pages 845--848. Springer International Publishing, 2016."},{"key":"key-10.1145\/2948992.2949022-6","doi-asserted-by":"crossref","unstructured":"Andranik Tumasjan, Timm Oliver Sprenger, Philipp G Sandner, and Isabell M Welpe. Predicting elections with twitter: What 140 characters reveal about political sentiment. ICWSM, 10, 2010.","DOI":"10.1609\/icwsm.v4i1.14009"},{"key":"key-10.1145\/2948992.2949022-7","unstructured":"Micol Marchetti-Bowick and Nathanael Chambers. Learning for microblogs with distant supervision: Political forecasting with twitter. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, EACL '12. Association for Computational Linguistics, 2012."},{"key":"key-10.1145\/2948992.2949022-8","doi-asserted-by":"crossref","unstructured":"Pawel Sobkowicz, Michael Kaschesky, and Guillaume Bouchard. Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web. Government Information Quarterly, 29(4):470--479, 2012. Social Media in Government - Selections from the 12th Annual International Conference on Digital Government Research.","DOI":"10.1016\/j.giq.2012.06.005"},{"key":"key-10.1145\/2948992.2949022-9","unstructured":"Avishay Livne, Matthew P Simmons, Eytan Adar, and Lada A Adamic. The party is over here: Structure and content in the 2010 election. In ICWSM, 2011."},{"key":"key-10.1145\/2948992.2949022-10","doi-asserted-by":"crossref","unstructured":"Andranik Tumasjan, Timm O Sprenger, Philipp G Sandner, and Isabell M Welpe. Predicting elections with twitter: What 140 characters reveal about political sentiment. In Proceedings of the fourth international AAAI conference on weblogs and social media, 2010.","DOI":"10.1609\/icwsm.v4i1.14009"},{"key":"key-10.1145\/2948992.2949022-11","doi-asserted-by":"crossref","unstructured":"D Gayo-Avello. I wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data. arXiv preprint arXiv:1204.6441, 2012.","DOI":"10.1109\/MIC.2012.137"},{"key":"key-10.1145\/2948992.2949022-12","doi-asserted-by":"crossref","unstructured":"Brendan O'Connor, Ramnath Balasubramanyan, Bryan R Routledge, and Noah A Smith. From tweets to polls: Linking text sentiment to public opinion time series. In Proceedings of the International AAAI Conference on Weblogs and Social Media, 2010.","DOI":"10.1609\/icwsm.v4i1.14031"},{"key":"key-10.1145\/2948992.2949022-13","doi-asserted-by":"crossref","unstructured":"Jessica Chung and Eni Mustafaraj. Can collective sentiment expressed on twitter predict political elections. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence. San Francisco, CA, USA, 2011.","DOI":"10.1609\/aaai.v25i1.8065"},{"key":"key-10.1145\/2948992.2949022-14","doi-asserted-by":"crossref","unstructured":"Harold Dwight Lasswell. The comparative study of symbols: An introduction. Number 1. Stanford University Press, 1952.","DOI":"10.1037\/14763-000"},{"key":"key-10.1145\/2948992.2949022-15","doi-asserted-by":"crossref","unstructured":"Maxwell E McCombs and Donald L Shaw. The agenda-setting function of mass media. Public opinion quarterly, 36(2), 1972.","DOI":"10.1086\/267990"},{"key":"key-10.1145\/2948992.2949022-16","doi-asserted-by":"crossref","unstructured":"Matthew C Moen. Ronald reagan and the social issues: Rhetorical support for the christian right. The Social Science Journal, 27(2):199--207, 1990.","DOI":"10.1016\/0362-3319(90)90036-J"},{"key":"key-10.1145\/2948992.2949022-17","doi-asserted-by":"crossref","unstructured":"Daniel Riffe and Alan Freitag. A content analysis of content analyses: Twenty-five years of journalism quarterly. Journalism & Mass Communication Quarterly, 74(3), 1997.","DOI":"10.1177\/107769909707400306"},{"key":"key-10.1145\/2948992.2949022-18","unstructured":"Kimberly A Neuendorf. The content analysis guidebook. Sage, 2002."},{"key":"key-10.1145\/2948992.2949022-19","doi-asserted-by":"crossref","unstructured":"Daniel J Hopkins and Gary King. A method of automated nonparametric content analysis for social science. American Journal of Political Science, 54(1), 2010.","DOI":"10.1111\/j.1540-5907.2009.00428.x"},{"key":"key-10.1145\/2948992.2949022-20","doi-asserted-by":"crossref","unstructured":"Justin Grimmer and Brandon M. Stewart. Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 2013.","DOI":"10.1093\/pan\/mps028"},{"key":"key-10.1145\/2948992.2949022-21","unstructured":"Panagiotis T. Metaxas, Eni Mustafaraj, and Dani Gayo-Avello. How (Not) to Predict Elections. 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing, October 2011."},{"key":"key-10.1145\/2948992.2949022-22","unstructured":"Daniel Gayo Avello, Panagiotis T Metaxas, and Eni Mustafaraj. Limits of electoral predictions using twitter. In Proceedings of the International Conference on Weblogs and Social Media, 2011."},{"key":"key-10.1145\/2948992.2949022-23","doi-asserted-by":"crossref","unstructured":"Daniel Gayo-Avello. A meta-analysis of state-of-the-art electoral prediction from twitter data. Social Science Computer Review, page 0894439313493979, 2013.","DOI":"10.1177\/0894439313493979"},{"key":"key-10.1145\/2948992.2949022-24","doi-asserted-by":"crossref","unstructured":"Bo Pang and Lillian Lee. Opinion mining and sentiment analysis. Found. Trends Inf. Retr., 2(1-2), 2008.","DOI":"10.1561\/1500000011"},{"key":"key-10.1145\/2948992.2949022-25","unstructured":"Efthymios Kouloumpis, Theresa Wilson, and Johanna Moore. Twitter sentiment analysis: The good the bad and the omg. In Proceedings of the International Conference on Weblogs and Social Media, 2011."},{"key":"key-10.1145\/2948992.2949022-26","unstructured":"Preslav Nakov, Sara Rosenthal, Zornitsa Kozareva, Veselin Stoyanov, Alan Ritter, and Theresa Wilson. Semeval-2013 task 2: Sentiment analysis in twitter. In Proceedings of the International Workshop on Semantic Evaluation (SemEval 2013), 2013."},{"key":"key-10.1145\/2948992.2949022-27","doi-asserted-by":"crossref","unstructured":"N. Diakopoulos and D. Shamma. Characterizing debate performance via aggregated twitter sentimen. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI'10, pages 1195--1198. ACM Press, April 2010.","DOI":"10.1145\/1753326.1753504"},{"key":"key-10.1145\/2948992.2949022-28","doi-asserted-by":"crossref","unstructured":"Pedro Saleiro, Silvio Amir, Mário Silva, and Carlos Soares. Popmine: Tracking political opinion on the web. In Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT\/IUCC\/DASC\/PICOM), 2015 IEEE International Conference on, pages 1521--1526. IEEE, 2015.","DOI":"10.1109\/CIT\/IUCC\/DASC\/PICOM.2015.228"},{"key":"key-10.1145\/2948992.2949022-29","unstructured":"Pedro Saleiro, Luıs Rei, Arian Pasquali, and Carlos Soares. Popstar at replab 2013: Name ambiguity resolution on twitter. In CLEF 2013 Eval. Labs and Workshop Online Working Notes, 2013."},{"key":"key-10.1145\/2948992.2949022-30","unstructured":"P. Metaxas, E. Mustafaraj, and D. Gayo-Avello. How (not) to predict elections. 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing, pages 165--171, October 2011."},{"key":"key-10.1145\/2948992.2949022-31","unstructured":"J. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, 2006."}],"event":{"name":"the Ninth International C* Conference","location":"Porto, Portugal","acronym":"C3S2E '16","number":"9","sponsor":["BytePress","ISEP"],"start":{"date-parts":[[2016,7,20]]},"end":{"date-parts":[[2016,7,22]]}},"container-title":["Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering - C3S2E '16"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2948992.2949022","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=2949022&ftid=1766643&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:55:59Z","timestamp":1750222559000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=2948992.2949022"}},"subtitle":[],"proceedings-subject":"Computer Science & Software Engineering","short-title":[],"issued":{"date-parts":[[2016]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1145\/2948992.2949022","relation":{},"subject":[],"published":{"date-parts":[[2016]]}}}