{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:42:15Z","timestamp":1743111735962,"version":"3.40.3"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031280757"},{"type":"electronic","value":"9783031280764"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-28076-4_27","type":"book-chapter","created":{"date-parts":[[2023,2,26]],"date-time":"2023-02-26T11:02:32Z","timestamp":1677409352000},"page":"358-374","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Stance Detection for\u00a0Gauging Public Opinion: A Statistical Analysis of\u00a0the\u00a0Difference Between Tweet-Based and\u00a0User-Based Stance in\u00a0Twitter"],"prefix":"10.1007","author":[{"given":"Ali","family":"Almadan","sequence":"first","affiliation":[]},{"given":"Mary Lou","family":"Maher","sequence":"additional","affiliation":[]},{"given":"Jason","family":"Windett","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"27_CR1","doi-asserted-by":"crossref","unstructured":"Aldayel, A., Magdy, W.: Your stance is exposed! Analysing possible factors for stance detection on social media. Proc. ACM Hum. Comput. Interact. 3(CSCW), 1\u201320 (2019)","DOI":"10.1145\/3359307"},{"issue":"4","key":"27_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102597","volume":"58","author":"Abeer ALDayel and Walid Magdy","year":"2021","unstructured":"Abeer ALDayel and Walid Magdy: Stance detection on social media: state of the art and trends. Inf. Process. Manag. 58(4), 102597 (2021)","journal-title":"Inf. Process. Manag."},{"key":"27_CR3","doi-asserted-by":"publisher","unstructured":"Almadan, A., Maher, M.L., Pereira, F.B., Guo, Y.: Will you be vaccinated? A methodology for annotating and analyzing Twitter data to measure the stance towards covid-19 vaccination. In: Arai, K. (ed.) Future of Information and Communication Conference, pp. 311\u2013329. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-98012-2_24","DOI":"10.1007\/978-3-030-98012-2_24"},{"key":"27_CR4","doi-asserted-by":"crossref","unstructured":"Atkinson, M.L., Elizabeth Coggins, K., Stimson, J.A., Baumgartner, F.R.: The Dynamics of Public Opinion. Elements in American Politics. Cambridge University Press (2021)","DOI":"10.1017\/9781108871266"},{"key":"27_CR5","doi-asserted-by":"crossref","unstructured":"Baly, R., Mohtarami, M., Glass, J., M\u00e0rquez, L., Moschitti, A., Nakov, P.: Integrating stance detection and fact checking in a unified corpus. arXiv preprint arXiv:1804.08012 (2018)","DOI":"10.18653\/v1\/N18-2004"},{"issue":"5","key":"27_CR6","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/MIS.2020.3044968","volume":"36","author":"A Bechini","year":"2020","unstructured":"Bechini, A., Ducange, P., Marcelloni, F., Renda, A.: Stance analysis of Twitter users: the case of the vaccination topic in Italy. IEEE Intell. Syst. 36(5), 131\u2013139 (2020)","journal-title":"IEEE Intell. Syst."},{"key":"27_CR7","doi-asserted-by":"crossref","unstructured":"Bourgonje, P., Schneider, J.M., Rehm, G.: From clickbait to fake news detection: an approach based on detecting the stance of headlines to articles. In: Proceedings of the 2017 EMNLP Workshop: Natural Language Processing Meets Journalism, pp. 84\u201389 (2017)","DOI":"10.18653\/v1\/W17-4215"},{"key":"27_CR8","doi-asserted-by":"crossref","unstructured":"Bovet, A., Morone, F., Makse, H.A.: Validation of twitter opinion trends with national polling aggregates: Hillary Clinton vs Donald Trump. Sci. Rep. 8(1), 1\u201316 (2018)","DOI":"10.1038\/s41598-018-26951-y"},{"key":"27_CR9","volume-title":"The American Voter","author":"A Campbell","year":"1960","unstructured":"Campbell, A., Converse, P.E., Miller, W.E., Stokes, D.E.: The American Voter. Wiley, New York (1960)"},{"issue":"2","key":"27_CR10","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1086\/265298","volume":"3","author":"HL Childs","year":"1939","unstructured":"Childs, H.L.: by public opinion i mean. Public Opin. Q. 3(2), 327\u2013336 (1939)","journal-title":"Public Opin. Q."},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"Chung, J.E., Mustafaraj, E.: Can collective sentiment expressed on twitter predict political elections? In: Twenty-fifth AAAI Conference on Artificial Intelligence (2011)","DOI":"10.1609\/aaai.v25i1.8065"},{"key":"27_CR12","unstructured":"Cody, E.M., Reagan, A.J., Dodds, P.S., Danforth, C.M.: Public opinion polling with twitter. arXiv preprint arXiv:1608.02024 (2016)"},{"key":"27_CR13","doi-asserted-by":"crossref","unstructured":"Cody, E.M., Reagan, A.J., Mitchell, L., Dodds, P.S., Danforth, C.M.: Climate change sentiment on Twitter: an unsolicited public opinion poll. PloS One 10(8), e0136092 (2015)","DOI":"10.1371\/journal.pone.0136092"},{"issue":"11","key":"27_CR14","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.3390\/sym13111995","volume":"13","author":"L-A Cotfas","year":"2021","unstructured":"Cotfas, L.-A., Delcea, C., Gherai, R., Roxin, I.: Unmasking people\u2019s opinions behind mask-wearing during covid-19 pandemic-a twitter stance analysis. Symmetry 13(11), 1995 (2021)","journal-title":"Symmetry"},{"issue":"3","key":"27_CR15","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/s10472-015-9488-0","volume":"77","author":"U Grandi","year":"2016","unstructured":"Grandi, U., Loreggia, A., Rossi, F., Saraswat, V.: A borda count for collective sentiment analysis. Ann. Math. Artif. Intell. 77(3), 281\u2013302 (2016)","journal-title":"Ann. Math. Artif. Intell."},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Gr\u010dar, M., Cherepnalkoski, D., Mozeti\u010d, I., Novak, P.K.: Stance and influence of Twitter users regarding the Brexit referendum. Comput. Soc. Netw. 4(1), 1\u201325 (2017)","DOI":"10.1186\/s40649-017-0042-6"},{"key":"27_CR17","doi-asserted-by":"crossref","unstructured":"Gunaratne, K., Coomes, E.A., Haghbayan, H.: Temporal trends in anti-vaccine discourse on Twitter. Vaccine 37(35), 4867\u20134871 (2019)","DOI":"10.1016\/j.vaccine.2019.06.086"},{"key":"27_CR18","doi-asserted-by":"crossref","unstructured":"Gupta, F., Singal, S.: Sentiment analysis of the demonitization of economy 2016 India, regionwise. In: 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence, pp. 693\u2013696. IEEE (2017)","DOI":"10.1109\/CONFLUENCE.2017.7943240"},{"key":"27_CR19","doi-asserted-by":"crossref","unstructured":"Hsieh, Y.L., Rak, S., SteelFisher, G.K., Bauhoff, S.: Effect of the suspension of the j &j covid-19 vaccine on vaccine hesitancy in the united states. Vaccine 40(3), 424\u2013427 (2022)","DOI":"10.1016\/j.vaccine.2021.11.085"},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Joseph, K.: (mis)alignment between stance expressed in social media data and public opinion surveys. arXiv preprint arXiv:2109.01762 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.27"},{"key":"27_CR21","doi-asserted-by":"crossref","unstructured":"Karami, A., Bennett, L.S., He, X.: Mining public opinion about economic issues: Twitter and the US presidential election. Int. J. Strateg. Decis. Sci. (IJSDS) 9(1), 18\u201328 (2018)","DOI":"10.4018\/IJSDS.2018010102"},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Kaunang, C.P.S., Amastini, F., Mahendra, R.: Analyzing stance and topic of e-cigarette conversations on Twitter: case study in Indonesia. In: 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0304\u20130310. IEEE (2021)","DOI":"10.1109\/CCWC51732.2021.9375949"},{"issue":"1","key":"27_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3369026","volume":"53","author":"D K\u00fc\u00e7\u00fck","year":"2020","unstructured":"K\u00fc\u00e7\u00fck, D., Can, F.: Stance detection: a survey. ACM Comput. Surv. (CSUR) 53(1), 1\u201337 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"27_CR24","doi-asserted-by":"crossref","unstructured":"Meg Lee, H.-H., van Dolen, W.: Creative participation: collective sentiment in online co-creation communities. Inf. Manag. 52(8), 951\u2013964 (2015)","DOI":"10.1016\/j.im.2015.07.002"},{"key":"27_CR25","unstructured":"Liu, B., et al.: Sentiment analysis and subjectivity. In: Handbook of Natural Language Processing, vol. 2, pp. 627\u2013666 (2010)"},{"key":"27_CR26","doi-asserted-by":"crossref","unstructured":"Amador\u00a0Diaz Lopez, J.C., Collignon-Delmar, S., Benoit, K., Matsuo, A.: Predicting the Brexit vote by tracking and classifying public opinion using twitter data. Stat. Polit. Policy 8(1), 85\u2013104 (2017)","DOI":"10.1515\/spp-2017-0006"},{"key":"27_CR27","doi-asserted-by":"crossref","unstructured":"Mahase, E.: Covid-19: us suspends Johnson and Johnson vaccine rollout over blood clots (2021)","DOI":"10.1136\/bmj.n970"},{"key":"27_CR28","doi-asserted-by":"crossref","unstructured":"Massey, F.J.,\u00a0Jr.: The Kolmogorov-Smirnov test for goodness of fit. J. Am. Stat. Assoc. 46(253), 68\u201378 (1951)","DOI":"10.1080\/01621459.1951.10500769"},{"key":"27_CR29","doi-asserted-by":"crossref","unstructured":"Mohammad, S., Kiritchenko, S., Sobhani, P., Zhu, X., Cherry, C.: Semeval-2016 task 6: detecting stance in tweets. In: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp. 31\u201341 (2016)","DOI":"10.18653\/v1\/S16-1003"},{"issue":"11","key":"27_CR30","doi-asserted-by":"publisher","DOI":"10.2196\/30642","volume":"7","author":"G Muric","year":"2021","unstructured":"Muric, G., Yusong, W., Ferrara, E., et al.: Covid-19 vaccine hesitancy on social media: building a public twitter data set of antivaccine content, vaccine misinformation, and conspiracies. JMIR Public Health Surveill. 7(11), e30642 (2021)","journal-title":"JMIR Public Health Surveill."},{"key":"27_CR31","doi-asserted-by":"crossref","unstructured":"Nguyen, L.T., Wu, P., Chan, W., Peng, W., Zhang, Y.: Predicting collective sentiment dynamics from time-series social media. In: Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining, pp. 1\u20138 (2012)","DOI":"10.1145\/2346676.2346682"},{"key":"27_CR32","doi-asserted-by":"crossref","unstructured":"Page, B.I., Shapiro, R.Y.: The Rational Public: Fifty Years of Trends in Americans\u2019 Policy Preferences. University of Chicago Press, Chicago (1992)","DOI":"10.7208\/chicago\/9780226644806.001.0001"},{"key":"27_CR33","doi-asserted-by":"crossref","unstructured":"Poddar, S., Mondal, M., Misra, J., Ganguly, N., Ghosh, S.: Winds of change: impact of covid-19 on vaccine-related opinions of twitter users. arXiv preprint arXiv:2111.10667 (2021)","DOI":"10.1609\/icwsm.v16i1.19334"},{"key":"27_CR34","unstructured":"Riedel, B., Augenstein, I., Spithourakis, G.P., Riedel, S.: A simple but tough-to-beat baseline for the fake news challenge stance detection task. arXiv preprint arXiv:1707.03264 (2017)"},{"key":"27_CR35","doi-asserted-by":"crossref","unstructured":"Samih, Y., Darwish., K.: A few topical tweets are enough for effective user stance detection. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pp. 2637\u20132646 (2021)","DOI":"10.18653\/v1\/2021.eacl-main.227"},{"key":"27_CR36","volume-title":"Public Opinion in America: Moods, Cycles, and Swings","author":"JA Stimson","year":"1999","unstructured":"Stimson, J.A.: Public Opinion in America: Moods, Cycles, and Swings, 2nd edn. Westview Press, Boulder (1999)","edition":"2"},{"key":"27_CR37","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511791024","volume-title":"Tides of Consent: How Public Opinion Shapes American Politics","author":"JA Stimson","year":"2004","unstructured":"Stimson, J.A.: Tides of Consent: How Public Opinion Shapes American Politics. Cambridge University Press, New York (2004)"},{"key":"27_CR38","doi-asserted-by":"crossref","unstructured":"Sullivan, G.M., Feinn, R.: Using effect size-or why the P value is not enough. J. Grad. Med. Educ. 4(3), 279\u2013282 (2012)","DOI":"10.4300\/JGME-D-12-00156.1"},{"key":"27_CR39","doi-asserted-by":"crossref","unstructured":"Tavoschi, L.: Twitter as a sentinel tool to monitor public opinion on vaccination: an opinion mining analysis from September 2016 to August 2017 in Italy. Hum. Vaccines Immunotherapeutics 16(5), 1062\u20131069 (2020)","DOI":"10.1080\/21645515.2020.1714311"},{"key":"27_CR40","doi-asserted-by":"crossref","unstructured":"Tumasjan, A., Sprenger, T., Sandner, P., Welpe, I.: Predicting elections with twitter: what 140 characters reveal about political sentiment. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 4, pp. 178\u2013185 (2010)","DOI":"10.1609\/icwsm.v4i1.14009"},{"key":"27_CR41","doi-asserted-by":"crossref","unstructured":"Umer, M., Imtiaz, Z., Ullah, S., Mehmood, A., Choi, G.S., On, B.-W.: Fake news stance detection using deep learning architecture (CNN-LSTM). IEEE Access 8, 156695\u2013156706 (2020)","DOI":"10.1109\/ACCESS.2020.3019735"},{"key":"27_CR42","doi-asserted-by":"crossref","unstructured":"Woolson, R.F.: Wilcoxon signed-rank test. In: Wiley Encyclopedia of Clinical Trials, pp. 1\u20133 (2007)","DOI":"10.1002\/9780471462422.eoct979"},{"key":"27_CR43","doi-asserted-by":"crossref","unstructured":"Xu, F., Keelj, V.: Collective sentiment mining of microblogs in 24-hour stock price movement prediction. In: 2014 IEEE 16th Conference on Business Informatics, vol.\u00a02, pp. 60\u201367. IEEE (2014)","DOI":"10.1109\/CBI.2014.37"},{"key":"27_CR44","doi-asserted-by":"crossref","unstructured":"Zaller, J.R., et\u00a0al.: The Nature and Origins of Mass Opinion. Cambridge University Press (1992)","DOI":"10.1017\/CBO9780511818691"}],"container-title":["Lecture Notes in Networks and Systems","Advances in Information and Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-28076-4_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T05:23:36Z","timestamp":1728969816000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-28076-4_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031280757","9783031280764"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-28076-4_27","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"27 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"FICC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Future of Information and Communication Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"San Francisco, CA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 March 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 March 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ficc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}