2017
DOI: 10.12785/ijcds/060203
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Mining Social Media Text: Extracting Knowledge from Facebook

Abstract: Social media websites allow users to communicate with each other through several tools like chats, discussion forums, comments etc. This results in learning and sharing of important information among the users. The nature of information on such social networking websites can be straight forward categorized as unstructured and fuzzy. In regular day-to-day discussions, spellings, grammar and sentence structure are usually neglected. This may prompt various sorts of ambiguities, for example, lexical, syntactic, a… Show more

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Cited by 50 publications
(6 citation statements)
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“…Supported by the social media mining methodological framework of Salloum et al (2017), the analysis steps mainly include information extraction, natural language processing, categorization, summarization, and visualization. Specifically, Louise Kennedy started blogging on Twitter in February 2011.…”
Section: Methodsmentioning
confidence: 99%
“…Supported by the social media mining methodological framework of Salloum et al (2017), the analysis steps mainly include information extraction, natural language processing, categorization, summarization, and visualization. Specifically, Louise Kennedy started blogging on Twitter in February 2011.…”
Section: Methodsmentioning
confidence: 99%
“…The application of the technology spans from social media knowledge extraction (A. Salloum, 2017), to analysing leadership behaviour in e-learning contexts (Xie et al, 2018) or conducting systematic literature reviews (Mergel et al, 2018).…”
Section: Methodsmentioning
confidence: 99%
“…On the data gathered, various text mining techniques were used. Findings showed that Fox News is the news outlet with the most Facebook postings shared, followed by CNN and ABC News, in that order [13].…”
Section: Data Mining On Social Mediamentioning
confidence: 99%