{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T13:33:07Z","timestamp":1758634387244},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,10,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Today, our more-than-ever digital lives leave significant footprints\nin cyberspace. Large scale collections of these socially generated\nfootprints, often known as big data, could help us to re-investigate\ndifferent aspects of our social collective behaviour in a quantitative\nframework. In this contribution we discuss one such possibility: the\nmonitoring and predicting of popularity dynamics of candidates and\nparties through the analysis of socially generated data on the web\nduring electoral campaigns.  Such data offer considerable possibility\nfor improving our awareness of popularity dynamics. However they also\nsuffer from significant drawbacks in terms of representativeness and\ngeneralisability. In this paper we discuss potential ways around such\nproblems, suggesting the nature of different political systems and\ncontexts might lend differing levels of predictive power to certain\ntypes of data source. We offer an initial exploratory test of these\nideas, focussing on two data streams, Wikipedia page views and Google\nsearch queries. On the basis of this data, we present popularity\ndynamics from real case examples of recent elections in three\ndifferent countries.<\/jats:p>","DOI":"10.1515\/itit-2014-1046","type":"journal-article","created":{"date-parts":[[2014,9,26]],"date-time":"2014-09-26T12:13:00Z","timestamp":1411733580000},"page":"246-253","source":"Crossref","is-referenced-by-count":12,"title":["Can electoral popularity be predicted using socially generated big data?"],"prefix":"10.1515","volume":"56","author":[{"given":"Taha","family":"Yasseri","sequence":"first","affiliation":[{"name":"Oxford Internet Institute, University of Oxford"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Bright","sequence":"additional","affiliation":[{"name":"Oxford Internet Institute, University of Oxford"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2014,9,30]]},"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1046\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1046\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T11:44:07Z","timestamp":1624448647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1046\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9,30]]},"references-count":0,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2014,9,30]]},"published-print":{"date-parts":[[2014,10,28]]}},"alternative-id":["10.1515\/itit-2014-1046"],"URL":"https:\/\/doi.org\/10.1515\/itit-2014-1046","relation":{},"ISSN":["1611-2776","2196-7032"],"issn-type":[{"value":"1611-2776","type":"print"},{"value":"2196-7032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,9,30]]}}}