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Devising Parametric User Models for Processing and Analysing Social Media Data to Influence User Behaviour: Using Quantitative and Qualitative Analysis of Social Media Data
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Author(s):
Jonathan Bishop
(Centre for Research into Online Communities and E-Learning Systems, UK)
Copyright:
2017
Pages:
41
Source title:
Social Media Data Extraction and Content Analysis
Source Author(s)/Editor(s):
Shalin Hai-Jew
(Hutchinson Community College, USA)
DOI:
10.4018/978-1-5225-0648-5.ch001
Keywords:
Data Mining
/
Information Science Reference
/
Library & Information Science
/
Social Computing
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Devising Parametric User Models for Processing and Analysing Social Media Data to Influence User Behaviour: Using Quantitative and Qualitative Analysis of Social Media Data
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Abstract
Academia is often plagued with those who define themselves by whether they are “quantitative” or “qualitative.” This chapter contests that when it comes to researching social media the two are inseparable in datafying user generated content. Posts on Twitter for instance have a textual element to the narratives that could be considered qualitative, but also quantitative criteria can be applied. Interviewing approaches can allow for the exploration of discourses to produce new theories, which may then rely of those approaches commonly thought of as quantitative. This chapter tests out a variety of different approaches to show how it is only through using all approaches available can social media be triangulated to produce accurate modelling of user behaviour.
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