This class will help you develop data mining and social media analysis skills using Python 3. It will also ask you to think critically about the ethical use of social media data. This is a hands-on, interdisciplinary data analytics class for those who have at least a casual familiarity with Python. If you haven’t taken a course on Python, you will want to complete “Learn Python the Hard Way” tutorials ($30) or a Codecademy course ($20-$40) on Python 3 on your own before this class. As a Digital Humanities course, it considers how social media has been used to support social justice and political change movements, the ways in which social media data is currently used by corporate entities, and engages in the discussion of ethical data usage. The course is organized around three projects that involve data collection, analysis, and presentation using the techniques learned in the class.
This course will guide you in developing fundamental digital research skills, including how to:
- Use different methods for collecting, analyzing, and exploring social media data for research and development purposes.
- Utilize various Application Programming Interface (API) services to collect data from different social media sources such as Twitter, Facebook, and more.
- Process the collected data – primarily structured – using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data.
- Analyze unstructured data – primarily textual comments – for themes and trends.
Matthew A. Russell & Mkihail Klassen, Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More, 3rd Edition (O’Reilly, 2019).
|Date||Pre-Class Actvity 1||Pre-Class Activity 2||In Class Activities||Assignments|
|4/4/2019||Read Mining the Social Web (MTSW), Preface, Appendices A-C. Follow any suggestions that will help you become more familiar with the technical aspects of our work.|
|4/9/2019||Read:||Read: Fiesler, Casey, and Nicholas Proferes. “‘Participant’ Perceptions of Twitter Research Ethics.” Social Media + Society, (January 2018).|
|4/11/2019||Run code from MTSW: 1.3.3 & 1.3.4 and add comments to explain what the code is doing.||Read: MTSW: 1.4.0.|
|4/16/2019||Listen (16min): Sheilah Kast & Jonna McKone, “The Politics of Archiving #BlackLivesMatter,” Maryland Morning with Sheilah Kast (15 May 2015).||Read: Whitelaw Reid, “Black Twitter 101: What is it? Where did it originate? Where is it headed?” UVa Today (28 November 2018).||Project pitches due|
|4/18/2019||Read: MTSW: 1.4.1 - 1.4.5||Read: Ed Summers, “Introducing Documenting the Now,” Maryland Institute for Technology in the Humanities (16 February 2016).||Twitter data for project|
|4/23/2019||Watch: Antony Funnel, “Meet the Digital Librarians Saving Social Media Posts to Protect Human Rights,” Future Tense (29 August 2017).||Read:|
|4/25/2019||Read: Ahmed Al-Rawi, “Assessing Public Sentiments and News Preferences on Al Jazeera and Al Arabiya,” (2017).||Sentiment Analysis Lesson in Jupyter notebook|
|4/30/2019||Read: Ahmed Al-Rawi, “Assessing Public Sentiments and News Preferences on Al Jazeera and Al Arabiya,” (2017).||Read: Bruns, “The Arab Spring and Social Media: English and Arabic Twitter Users and Their Networks” (2013).|
|5/2/2019||Continue working on project 1.||Continue working on project 1. Troubleshoot challenges.|
|5/7/2019||Read: Bruns, “The Arab Spring and Social Media: English and Arabic Twitter Users and Their Networks” (2013).||Continue working on project 1. Troubleshoot challenges.|
|5/9/2109||Continue working on project 1||Continue working on project 1. Troubleshoot challenges.||Project 1 – Twitter
|5/14/2019||Team Project Lightning Talks||Project 1 Team Lightning Talk|
|5/16/2019||Read: Ahmed Al-Rawi, “Framing the Online Women’s Movements in the Arab World,” (2014).||Qualitative data analysis tutorial with Voyant Tools & Python|
|5/21/2019||Read: MTSW 5.4 “Querying Human Language Data with TF-IDF”. Read this entire section, including the code.|
|5/23/2019||Read: MTSW: 5.4.4, 5.4.5, 5.5||Project 2 Pitches Due|
|5/28/2019||Read: MTSW: chapter 6||Read: Hinds, “What Demographic Attributes Do Our Digital Footprints Reveal? A Systematic Review” (2018).|
|5/30/2019||Work on Project 2. Troubleshoot challenges|
|6/4/2019||Project 3: Lightning Talks - Share findings, visualizations, challenges & peer feedback. Strengths, suggestions.|
|6/13/2019||Project 2: Web scraping & qualitative data analysis