Social Media Data Analysis
Dates: 27 October 2017, 28 May 2018
Instructor: Mike Thelwall
Fee: £195 (£140 for those from educational, government and charitable institutions).
We offer up to 5 subsidised places at a reduced rate of £60 per course to research staff and students within Humanities at the University of Manchester. These places are awarded in order of application. In some instances, such as for unfunded PhD students, we may be able to offer free or bursary places.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
This course describes how to use free Windows software Mozdeh to gather tweets and to download comments on YouTube videos. The course will also describe simple methods to gain insights into the meaning of the downloaded texts and to identify patterns within the data.
You will learn to use the free Mozdeh Windows software to:
- Gather tweets from a set of named users or tweets matching one or more keyword queries.
- Gather comments on one or more YouTube videos.
- Analyse the texts with simple big data methods: word association mining, gender, sentiment and time difference detection and association mining, time series graphs and networks of user interactions.
- Analyse the texts with content analysis.
Participants should have a basic familiarity with YouTube and Twitter, and be prepared to learn to use new software. Familiarity with Microsoft Windows.
Thelwall, M., Goriunova, O. Vis, F., Faulkner, S., Burns, A., Aulich, J. Mas-Bleda, A., Stuart, E. & D’Orazio, F. (2016). Chatting through pictures? A classification of images tweeted in one week in the UK and USA. Journal of the Association for Information Science and Technology, 67(11), 2575-2586.
Wilkinson, D. & Thelwall, M. (2012). Trending Twitter topics in English: An international comparison. Journal of the American Society for Information Science and Technology, 63(8), 1631-1646.
Thelwall, M., Sud, P., & Vis, F. (2012). Commenting on YouTube videos: From Guatemalan rock to El Big Bang. Journal of the American Society for Information Science and Technology, 63(3), 616–629.
About the instructor
Mike Thelwall is a professor of Information Science and head of the Statistical Cybermetrics Research Group at the University of Wolverhampton. He researching big data, webometrics, social media metrics, and sentiment analysis; developing quantitative web methods for Twitter, social networks, YouTube, and various types of link and impact metrics; conducting impact assessments for organisations, such as the UNDP.