{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:46:20Z","timestamp":1742942780146,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030607029"},{"type":"electronic","value":"9783030607036"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-60703-6_65","type":"book-chapter","created":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T07:03:05Z","timestamp":1604732585000},"page":"500-508","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Diabetweets: Analysis of Tweets for Health-Related Information"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9247-8682","authenticated-orcid":false,"given":"Hamzah","family":"Osop","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rabiul","family":"Hasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chei Sian","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chee Yong","family":"Neo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chee Kim","family":"Foo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ankit","family":"Saurabh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,8]]},"reference":[{"issue":"23","key":"65_CR1","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1001\/jama.2015.5287","volume":"313","author":"FB Hu","year":"2015","unstructured":"Hu, F.B., Satija, A., Manson, J.E.: Curbing the diabetes pandemic: the need for global policy solutions. JAMA 313(23), 2319\u20132320 (2015)","journal-title":"JAMA"},{"key":"65_CR2","doi-asserted-by":"publisher","first-page":"107843","DOI":"10.1016\/j.diabres.2019.107843","volume":"157","author":"P Saeedi","year":"2019","unstructured":"Saeedi, P., et al.: Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the international diabetes federation diabetes atlas. Diabetes Res. Clin. Pract. 157, 107843 (2019)","journal-title":"Diabetes Res. Clin. Pract."},{"key":"65_CR3","unstructured":"Data.gov.sg. Prevalence of hypertension, diabetes, high total cholesterol, obesity and daily smoking (2020). [cited 2020]. https:\/\/data.gov.sg\/dataset\/prevalence-of-hypertension-diabetes-high-total-cholesterol-obesity-and-daily-smoking?view_id=36a54ebf-3db6-48c8-84c8-c15e48ed5c0a&resource_id=c5f26f19-b6aa-4f4f-ae5b-ee62d840f8e7"},{"key":"65_CR4","unstructured":"Jung, A.-K., Mirbabaie, M., Ross, B., Stieglitz, S., Neuberger, C., Kapidzic, S. Information diffusion between Twitter and online media (2018)"},{"issue":"6","key":"65_CR5","doi-asserted-by":"publisher","first-page":"121","DOI":"10.3390\/jcm7060121","volume":"7","author":"Y Pershad","year":"2018","unstructured":"Pershad, Y., Hangge, P.T., Albadawi, H., Oklu, R.: Social medicine: Twitter in healthcare. J. Clin. Med. 7(6), 121 (2018)","journal-title":"J. Clin. Med."},{"key":"65_CR6","unstructured":"Statista. Most popular social networks as of January 2020, ranked by number of active users (2020). https:\/\/www.statista.com\/statistics\/272014\/global-social-networks-ranked-by-number-of-users\/"},{"key":"65_CR7","unstructured":"Mention. Twitter engagement report 2018 (2018)"},{"issue":"10","key":"65_CR8","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1177\/0193945914565056","volume":"37","author":"D Finfgeld-Connett","year":"2015","unstructured":"Finfgeld-Connett, D.: Twitter and health science research. West. J. Nurs. Res. 37(10), 1269\u20131283 (2015)","journal-title":"West. J. Nurs. Res."},{"issue":"3","key":"65_CR9","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1177\/1932296818811679","volume":"13","author":"E Gabarron","year":"2019","unstructured":"Gabarron, E., Dorronzoro, E., Rivera-Romero, O., Wynn, R.: Diabetes on Twitter: a sentiment analysis. J Diab. Sci Technol. 13(3), 439\u2013444 (2019)","journal-title":"J Diab. Sci Technol."},{"key":"65_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1200\/CCI.18.00088","volume":"3","author":"MS Sedrak","year":"2019","unstructured":"Sedrak, M.S., et al.: Examining public communication about kidney cancer on Twitter. JCO Clin. Cancer Inform. 3, 1\u20136 (2019)","journal-title":"JCO Clin. Cancer Inform."},{"issue":"1","key":"65_CR11","doi-asserted-by":"publisher","first-page":"e1","DOI":"10.2105\/AJPH.2016.303512","volume":"107","author":"L Sinnenberg","year":"2017","unstructured":"Sinnenberg, L., Buttenheim, A.M., Padrez, K., Mancheno, C., Ungar, L., Merchant, R.M.: Twitter as a tool for health research: a systematic review. Am. J. Public Health 107(1), e1\u2013e8 (2017)","journal-title":"Am. J. Public Health"},{"key":"65_CR12","doi-asserted-by":"crossref","unstructured":"Joyce, B., Deng, J.: Sentiment analysis of tweets for the 2016 US presidential election. In: 2017 IEEE MIT Undergraduate Research Technology Conference (URTC) (2017)","DOI":"10.1109\/URTC.2017.8284176"},{"key":"65_CR13","doi-asserted-by":"crossref","unstructured":"Rane, A., Kumar, A.: Sentiment classification system of Twitter data for US airline service analysis. In: 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC) (2018)","DOI":"10.1109\/COMPSAC.2018.00114"},{"key":"65_CR14","doi-asserted-by":"crossref","unstructured":"Rathi, M., Malik, A., Varshney, D., Sharma, R., Mendiratta, S. Sentiment analysis of Tweets using machine learning approach. In: 2018 Eleventh International Conference on Contemporary Computing (IC3) (2018)","DOI":"10.1109\/IC3.2018.8530517"},{"key":"65_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1007\/978-3-319-46963-8_7","volume-title":"Current Trends in Web Engineering","author":"P Missier","year":"2016","unstructured":"Missier, P., et al.: Tracking dengue epidemics using Twitter content classification and topic modelling. In: Casteleyn, S., Dolog, P., Pautasso, C. (eds.) ICWE 2016. LNCS, vol. 9881, pp. 80\u201392. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46963-8_7"},{"issue":"3","key":"65_CR16","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.pcad.2017.09.001","volume":"60","author":"ME Herman","year":"2017","unstructured":"Herman, M.E., O\u2019Keefe, J.H., Bell, D.S.H., Schwartz, S.S.: Insulin therapy increases cardiovascular risk in type 2 diabetes. Prog. Cardiovasc. Dis. 60(3), 422\u2013434 (2017)","journal-title":"Prog. Cardiovasc. Dis."},{"key":"65_CR17","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.jcjd.2020.01.003","volume":"44","author":"M De Paoli","year":"2020","unstructured":"De Paoli, M., Werstuck, G.H.: Role of estrogen in type 1 and type 2 diabetes mellitus: a review of clinical and preclinical data. Can. J. Diab. 44, 448\u2013452 (2020)","journal-title":"Can. J. Diab."},{"issue":"1","key":"65_CR18","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1111\/nyas.12355","volume":"1311","author":"S Reutrakul","year":"2014","unstructured":"Reutrakul, S., Van Cauter, E.: Interactions between sleep, circadian function, and glucose metabolism: implications for risk and severity of diabetes. Ann. N. Y. Acad. Sci. 1311(1), 151\u2013173 (2014)","journal-title":"Ann. N. Y. Acad. Sci."},{"issue":"7","key":"65_CR19","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1038\/nm.4350","volume":"23","author":"MP Czech","year":"2017","unstructured":"Czech, M.P.: Insulin action and resistance in obesity and type 2 diabetes. Nat. Med. 23(7), 804\u2013814 (2017)","journal-title":"Nat. Med."},{"issue":"7","key":"65_CR20","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1016\/j.numecd.2017.02.004","volume":"27","author":"V Sordi","year":"2017","unstructured":"Sordi, V., et al.: Stem cells to restore insulin production and cure diabetes. Nutr. Metab. Cardiovasc. Dis. 27(7), 583\u2013600 (2017)","journal-title":"Nutr. Metab. Cardiovasc. Dis."}],"container-title":["Communications in Computer and Information Science","HCI International 2020 \u2013 Late Breaking Posters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60703-6_65","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:03:31Z","timestamp":1730592211000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60703-6_65"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030607029","9783030607036"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60703-6_65","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"8 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Copenhagen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denmark","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2020.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}