Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/3034
DC FieldValueLanguage
dc.contributor.authorMillham, Richard-
dc.date.accessioned2018-06-06T07:49:54Z-
dc.date.available2018-06-06T07:49:54Z-
dc.date.issued2016-
dc.identifier.citationMIllham, R. 2016. Theme evolution and structure in Twitter : a case study of South African student protests of 2015. 2016 IEEE International Conference on Big Data Analysis (ICBDA). :1-4.en_US
dc.identifier.isbn978-1-4673-9591-5 (online)-
dc.identifier.isbn978-1-4673-9590-8 (print)-
dc.identifier.isbn978-1-4673-9589-2 (CD-
dc.identifier.isbn978-1-4673-9592-2 (PoD)-
dc.identifier.urihttp://hdl.handle.net/10321/3034-
dc.description.abstractSocial media, based on human interactions, often has constantly changing foci, or themes, within their interactions. These themes, frequently used to categorize information within this social media, often evolve dependent on time, domain, and event contexts. Using a case study of South African student protests during a short but eventful time period in 2015, this paper analyses numerous tweets made to selected hashtags (one national and two local) in order to determine relevant themes within these tweets and to determine how these themes evolved, both at the national and local level, given their context. It was discovered that, as certain events unfolded, certain themes varied in prominence and locally-based hashtags converged into nationally-based hashtags reflecting a change in the nature of the protests.en_US
dc.format.extent4 pen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectTheme evolutionen_US
dc.subjectTweetsen_US
dc.subjectStudent protestsen_US
dc.subjectSocial Mediaen_US
dc.titleTheme evolution and structure in Twitter : a case study of South African student protests of 2015en_US
dc.typePresentationen_US
dc.publisher.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7509828en_US
dc.dut-rims.pubnumDUT-005339en_US
dc.description.availabilityCopyright: 2016. IEEE. Due to copyright restrictions, only the abstract is available. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in 2016 IEEE International Conference on Big Data Analysis (ICBDA). 4 Pages. https://ieeexplore.ieee.org/document/7509828en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypePresentation-
item.grantfulltextnone-
item.cerifentitytypePublications-
Appears in Collections:Research Publications (Accounting and Informatics)
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