{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T16:59:38Z","timestamp":1777741178240,"version":"3.51.4"},"reference-count":49,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IP"],"published-print":{"date-parts":[[2021,12,6]]},"abstract":"<jats:p>In this paper, we perform sentiment analysis and topic modeling on Twitter and Facebook posts of nine public sector organizations operating in Northeast US. The study objective is to compare and contrast message sentiment, content and topics of discussion on social media. We discover that sentiment and frequency of messages on social media is indeed affected by nature of organization\u2019s operations. We also discover that organizations either use Twitter for broadcasting or one-to-one communication with public. Finally we found discussion topics of organizations \u2013 identified through unsupervised machine learning \u2013 that engaged in similar areas of public service having similar topics and keywords in their public messages. Our analysis also indicates missed opportunities by these organizations when communication with public. Findings from this study can be used by public sector entities to understand and improve their social media engagement with citizens.<\/jats:p>","DOI":"10.3233\/ip-210321","type":"journal-article","created":{"date-parts":[[2021,7,20]],"date-time":"2021-07-20T12:55:08Z","timestamp":1626785708000},"page":"375-390","source":"Crossref","is-referenced-by-count":5,"title":["Analyzing social media messages of public sector organizations utilizing sentiment analysis and topic modeling"],"prefix":"10.1177","volume":"26","author":[{"given":"Ussama","family":"Yaqub","sequence":"first","affiliation":[{"name":"Lahore University of Management Sciences, Lahore, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soon Ae","family":"Chun","sequence":"additional","affiliation":[{"name":"City University of New York, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijayalakshmi","family":"Atluri","sequence":"additional","affiliation":[{"name":"Rutgers Business School, Newark, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jaideep","family":"Vaidya","sequence":"additional","affiliation":[{"name":"Rutgers Business School, Newark, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/IP-210321_ref1","doi-asserted-by":"crossref","unstructured":"Anwar, A., Ilyas, H., Yaqub, U., & Zaman, S. (2021). Analyzing qanon on twitter in context of us elections 2020: Analysis of user messages and profiles using vader and bert topic modeling. In DG. O2021: The 22nd Annual International Conference on Digital Government Research, pp. 82-88.","DOI":"10.1145\/3463677.3463718"},{"key":"10.3233\/IP-210321_ref2","doi-asserted-by":"crossref","unstructured":"Anwar, A., & Yaqub, U. (2020). Bot detection in twitter landscape using unsupervised learning. In The 21st Annual International Conference on Digital Government Research, pp. 329-330.","DOI":"10.1145\/3396956.3401801"},{"issue":"3","key":"10.3233\/IP-210321_ref3","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.giq.2010.03.001","article-title":"Using icts to create a culture of transparency: e-government and social media as openness and anti-corruption tools for societies","volume":"27","author":"Bertot","year":"2010","journal-title":"Government Information Quarterly"},{"issue":"11","key":"10.3233\/IP-210321_ref4","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/MC.2010.325","article-title":"Social media technology and government transparency","volume":"43","author":"Bertot","year":"2010","journal-title":"Computer"},{"key":"10.3233\/IP-210321_ref5","doi-asserted-by":"crossref","unstructured":"Blei, D.M., & Lafferty, J.D. (2006). Dynamic topic models. In Proceedings of the 23rd International Conference on Machine Learning, pp. 113-120.","DOI":"10.1145\/1143844.1143859"},{"key":"10.3233\/IP-210321_ref6","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"the Journal of Machine Learning Research"},{"key":"10.3233\/IP-210321_ref7","doi-asserted-by":"crossref","unstructured":"Calderon, N.A., Fisher, B., Hemsley, J., Ceskavich, B., Jansen, G., Marciano, R., & Lemieux, V.L. (2015). Mixed-initiative social media analytics at the world bank: Observations of citizen sentiment in twitter data to explore \u201ctrust\u201d of political actors and state institutions and its relationship to social protest. In Big Data (Big Data), 2015 IEEE International Conference on, IEEE, pp. 1678-1687.","DOI":"10.1109\/BigData.2015.7363939"},{"issue":"4","key":"10.3233\/IP-210321_ref8","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1111\/j.1468-0491.2009.01451.x","article-title":"The transparency president? The obama administration and open government","volume":"22","author":"Coglianese","year":"2009","journal-title":"Governance"},{"issue":"2","key":"10.3233\/IP-210321_ref9","doi-asserted-by":"crossref","first-page":"2","DOI":"10.5038\/2375-0901.16.2.2","article-title":"A novel transit rider satisfaction metric: rider sentiments measured from online social media data","volume":"16","author":"Collins","year":"2013","journal-title":"Journal of Public Transportation"},{"key":"10.3233\/IP-210321_ref10","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1016\/j.trc.2017.02.008","article-title":"Tweeting transit: an examination of social media strategies for transport information management during a large event","volume":"77","author":"Cottrill","year":"2017","journal-title":"Transportation Research Part C: Emerging Technologies"},{"issue":"1","key":"10.3233\/IP-210321_ref11","first-page":"10","article-title":"Social media and police leadership: lessons from boston","volume":"6","author":"Davis","year":"2014","journal-title":"Australasian Policing"},{"issue":"2","key":"10.3233\/IP-210321_ref12","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.intmar.2012.01.003","article-title":"Popularity of brand posts on brand fan pages: an investigation of the effects of social media marketing","volume":"26","author":"De Vries","year":"2012","journal-title":"Journal of Interactive Marketing"},{"key":"10.3233\/IP-210321_ref13","doi-asserted-by":"crossref","unstructured":"Denef, S., Bayerl, P.S., & Kaptein, N.A. (2013). Social media and the police: tweeting practices of british police forces during the august 2011 riots. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, pp.\u00a03471-3480.","DOI":"10.1145\/2470654.2466477"},{"issue":"11","key":"10.3233\/IP-210321_ref15","doi-asserted-by":"crossref","first-page":"e0142390","DOI":"10.1371\/journal.pone.0142390","article-title":"Measuring emotional contagion in social media","volume":"10","author":"Ferrara","year":"2015","journal-title":"PloS One"},{"key":"10.3233\/IP-210321_ref16","doi-asserted-by":"crossref","first-page":"e26","DOI":"10.7717\/peerj-cs.26","article-title":"Quantifying the effect of sentiment on information diffusion in social media","volume":"1","author":"Ferrara","year":"2015","journal-title":"PeerJ Computer Science"},{"issue":"4","key":"10.3233\/IP-210321_ref18","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1111\/puar.12378","article-title":"Does twitter increase perceived police legitimacy","volume":"75","author":"Grimmelikhuijsen","year":"2015","journal-title":"Public Administration Review"},{"issue":"2","key":"10.3233\/IP-210321_ref19","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1177\/1077699016639231","article-title":"Big social data analytics in journalism and mass communication: comparing dictionary-based text analysis and unsupervised topic modeling","volume":"93","author":"Guo","year":"2016","journal-title":"Journalism & Mass Communication Quarterly"},{"issue":"1","key":"10.3233\/IP-210321_ref20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/meet.14504701277","article-title":"Twitter for city police department information sharing","volume":"47","author":"Heverin","year":"2010","journal-title":"Proceedings of the Association for Information Science and Technology"},{"key":"10.3233\/IP-210321_ref21","doi-asserted-by":"crossref","unstructured":"Hou, Y., & Lampe, C. (2015). Social media effectiveness for public engagement: Example of small nonprofits. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ACM, pp. 3107-3116.","DOI":"10.1145\/2702123.2702557"},{"key":"10.3233\/IP-210321_ref22","doi-asserted-by":"crossref","unstructured":"Huang, Y., Wu, Q., & Hou, Y. (2017). Examining twitter mentions between police agencies and public users through the lens of stakeholder theory. In Proceedings of the 18th Annual International Conference on Digital Government Research, ACM, pp.\u00a030-38.","DOI":"10.1145\/3085228.3085316"},{"key":"10.3233\/IP-210321_ref23","doi-asserted-by":"crossref","unstructured":"Ilyas, S.H.W., Soomro, Z.T., Anwar, A., Shahzad, H., & Yaqub, U. (2020). Analyzing brexit\u2019s impact using sentiment analysis and topic modeling on twitter discussion. In The 21st Annual International Conference on Digital Government Research, pp.\u00a01-6.","DOI":"10.1145\/3396956.3396973"},{"issue":"11","key":"10.3233\/IP-210321_ref24","doi-asserted-by":"crossref","first-page":"15169","DOI":"10.1007\/s11042-018-6894-4","article-title":"Latent dirichlet allocation (lda) and topic modeling: models, applications, a survey","volume":"78","author":"Jelodar","year":"2019","journal-title":"Multimedia Tools and Applications"},{"issue":"10","key":"10.3233\/IP-210321_ref25","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1016\/j.jbusres.2011.10.014","article-title":"Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand","volume":"65","author":"Kim","year":"2012","journal-title":"Journal of Business Research"},{"issue":"4","key":"10.3233\/IP-210321_ref26","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1016\/j.giq.2012.06.001","article-title":"An open government maturity model for social media-based public engagement","volume":"29","author":"Lee","year":"2012","journal-title":"Government Information Quarterly"},{"issue":"2","key":"10.3233\/IP-210321_ref27","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.ijtst.2016.09.005","article-title":"Understanding social media program usage in public transit agencies","volume":"5","author":"Liu","year":"2016","journal-title":"International Journal of Transportation Science and Technology"},{"key":"10.3233\/IP-210321_ref28","doi-asserted-by":"crossref","unstructured":"Lorenzi, D., Vaidya, J., Shafiq, B., Chun, S., Vegesna, N., Alzamil, Z., Adam, N., Wainer, S., & Atluri, V. (2014). Utilizing social media to improve local government responsiveness. In Proceedings of the 15th Annual International Conference on Digital Government Research, ACM, pp. 236-244.","DOI":"10.1145\/2612733.2612773"},{"issue":"2","key":"10.3233\/IP-210321_ref29","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.pubrev.2012.01.005","article-title":"Engaging stakeholders through twitter: how nonprofit organizations are getting more out of 140 characters or less","volume":"38","author":"Lovejoy","year":"2012","journal-title":"Public Relations Review"},{"issue":"2-3","key":"10.3233\/IP-210321_ref30","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1080\/19312458.2018.1430754","article-title":"Applying lda topic modeling in communication research: toward a valid and reliable methodology","volume":"12","author":"Maier","year":"2018","journal-title":"Communication Methods and Measures"},{"issue":"1","key":"10.3233\/IP-210321_ref31","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1177\/1461444810365313","article-title":"I tweet honestly, i tweet passionately: twitter users, context collapse, and the imagined audience","volume":"13","author":"Marwick","year":"2011","journal-title":"New Media & Society"},{"issue":"4","key":"10.3233\/IP-210321_ref32","doi-asserted-by":"crossref","first-page":"04018007","DOI":"10.1061\/JTEPBS.0000128","article-title":"Utilizing social media in transport planning and public transit quality: survey of literature","volume":"144","author":"Nikolaidou","year":"2018","journal-title":"Journal of Transportation Engineering, Part A: Systems"},{"key":"10.3233\/IP-210321_ref33","doi-asserted-by":"crossref","unstructured":"Ramage, D., Hall, D., Nallapati, R., & Manning, C.D. (2009). Labeled lda: A supervised topic model for credit attribution in multi-labeled corpora. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pp.\u00a0248-256.","DOI":"10.3115\/1699510.1699543"},{"issue":"1","key":"10.3233\/IP-210321_ref34","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1080\/15228835.2019.1616350","article-title":"A computational social science perspective on qualitative data exploration: using topic models for the descriptive analysis of social media data","volume":"38","author":"Rodriguez","year":"2020","journal-title":"Journal of Technology in Human Services"},{"issue":"3","key":"10.3233\/IP-210321_ref35","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.pubrev.2013.02.005","article-title":"The effects of organizational twitter interactivity on organization-public relationships","volume":"39","author":"Saffer","year":"2013","journal-title":"Public Relations Review"},{"issue":"4","key":"10.3233\/IP-210321_ref36","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1109\/TKDE.2012.29","article-title":"Tweet analysis for real-time event detection and earthquake reporting system development","volume":"25","author":"Sakaki","year":"2013","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"10.3233\/IP-210321_ref37","doi-asserted-by":"crossref","first-page":"18","DOI":"10.31046\/tl.v11i1.506","article-title":"A gentle introduction to topic modeling using python","volume":"11","author":"Saxton","year":"2018","journal-title":"Theological Librarianship"},{"issue":"3","key":"10.3233\/IP-210321_ref38","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1080\/01944363.2014.980439","article-title":"Planning and social media: a case study of public transit and stigma on twitter","volume":"80","author":"Schweitzer","year":"2014","journal-title":"Journal of the American Planning Association"},{"key":"10.3233\/IP-210321_ref39","doi-asserted-by":"crossref","unstructured":"Sharma, N., Pabreja, R., Yaqub, U., Atluri, V., Chun, S., & Vaidya, J. (2018). Web-based application for sentiment analysis of live tweets. In Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, ACM, p. 120.","DOI":"10.1145\/3209281.3209402"},{"key":"10.3233\/IP-210321_ref41","doi-asserted-by":"crossref","unstructured":"Shwartz-Asher, D., Chun, S., & Adam, N.R. (2016). Social media user behavior analysis in e-government context. In Proceedings of the 17th International Digital Government Research Conference on Digital Government Research, ACM, pp. 39-48.","DOI":"10.1145\/2912160.2912188"},{"key":"10.3233\/IP-210321_ref45","doi-asserted-by":"crossref","unstructured":"Subba, R., & Bui, T. (2017). Online convergence behavior, social media communications and crisis response: An empirical study of the 2015 nepal earthquake police twitter project. In Proceedings of the 50th Hawaii International Conference on System Sciences.","DOI":"10.24251\/HICSS.2017.034"},{"issue":"4","key":"10.3233\/IP-210321_ref46","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1007\/s11280-014-0299-8","article-title":"Locating targets through mention in twitter","volume":"18","author":"Tang","year":"2015","journal-title":"World Wide Web"},{"issue":"2","key":"10.3233\/IP-210321_ref47","first-page":"406","article-title":"Sentiment in twitter events","volume":"62","author":"Thelwall","year":"2011","journal-title":"Journal of the Association for Information Science and Technology"},{"issue":"12","key":"10.3233\/IP-210321_ref48","first-page":"2544","article-title":"Sentiment strength detection in short informal text","volume":"61","author":"Thelwall","year":"2010","journal-title":"Journal of the Association for Information Science and Technology"},{"issue":"1","key":"10.3233\/IP-210321_ref49","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1609\/icwsm.v4i1.14009","article-title":"Predicting elections with twitter: what 140 characters reveal about political sentiment","volume":"10","author":"Tumasjan","year":"2010","journal-title":"ICWSM"},{"issue":"1","key":"10.3233\/IP-210321_ref51","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s11069-017-2960-x","article-title":"Crisis information distribution on twitter: a content analysis of tweets during hurricane sandy","volume":"89","author":"Wang","year":"2017","journal-title":"Natural Hazards"},{"issue":"4","key":"10.3233\/IP-210321_ref52","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1002\/pa.385","article-title":"Squawking, tweeting, cooing, and hooting: analyzing the communication patterns of government agencies on twitter","volume":"11","author":"Waters","year":"2011","journal-title":"Journal of Public Affairs"},{"issue":"2","key":"10.3233\/IP-210321_ref53","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.giq.2018.03.001","article-title":"Leveraging social media to achieve a community policing agenda","volume":"35","author":"Williams","year":"2018","journal-title":"Government Information Quarterly"},{"issue":"4","key":"10.3233\/IP-210321_ref54","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1016\/j.giq.2017.11.001","article-title":"Analysis of political discourse on twitter in the context of the 2016 us presidential elections","volume":"34","author":"Yaqub","year":"2017","journal-title":"Government Information Quarterly"},{"issue":"2","key":"10.3233\/IP-210321_ref55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3339909","article-title":"Location-based sentiment analyses and visualization of twitter election data","volume":"1","author":"Yaqub","year":"2020","journal-title":"Digital Government: Research and Practice"},{"issue":"1","key":"10.3233\/IP-210321_ref56","first-page":"44","article-title":"Facebook, twitter, and blogs: the adoption and utilization of social media in nonprofit human service organizations","volume":"41","author":"Young","year":"2017","journal-title":"Human Service Organizations: Management, Leadership & Governance"}],"container-title":["Information Polity"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/IP-210321","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T11:28:31Z","timestamp":1777462111000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/IP-210321"}},"subtitle":[],"editor":[{"given":"Rodrigo","family":"Sandoval-Almazan","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Andrea","family":"Kavanaugh","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"J.","family":"Ignacio Criado","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,12,6]]},"references-count":49,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/ip-210321","relation":{},"ISSN":["1570-1255","1875-8754"],"issn-type":[{"value":"1570-1255","type":"print"},{"value":"1875-8754","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,6]]}}}