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Cathie Marsh Institute for Social Research (CMI)

Social Media for Data Analysis

Dates: 23 November 2018 and 24 May 2019

Time: 9:45am - 17:00pm

Instructor: Mike Thelwall

Level: Introductory 

Fee: £195 (£140 for those from educational, government and charitable institutions). 

CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application. 

Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.

Please contact Joshua Edgar (email: for a Bursary application form for any general course enquires please contact

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 is important too.

Recommended reading

  • Thelwall, M. (2018). Social media analytics for YouTube comments: Potential and limitations. International Journal of Social Research Methodology, 21(3), 303-316.
  • Thelwall, M. & Mas-Bleda, A. (2018). YouTube science channel video presenters and comments: Female friendly or vestiges of sexism? Aslib Journal of Information Management, 70(1), 28-46.
  • Thelwall, M. & Cugelman, B. (2017). Monitoring Twitter strategies to discover resonating topics: the case of the UNDP. El Profesional de la Información, 26(4), 649-661.

About the instructor

Mike Thelwall is a professor of Data 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.