#SocialHumanities Datahack: Self-(Re)presentations on Social Media
How do people represent themselves on social media, and how are they represented by others? Which qualities and virtues are emphasized (or ignored)? How polarised are these (re)presentations?
The TORCH #SocialHumanities network will explore answers to these questions at our day-long datahack on 14 January, by examining content from YouTube, Twitter, Facebook, Instagram, Wikipedia, Reddit, and other social media platforms. We welcome participants from all disciplines, including the humanities and both social and computational sciences.
In the morning we will have four expert-led workshops, where specific approaches to social media data analysis will be taught, followed by lunch and the datahack proper. During lunch, participants will split into interdisciplinary teams (of two to four people) and decide upon which dataset to explore and which research question to answer. Datasets and questions will be provided, but you are more than welcome to bring your own (we’re both BYOD and BYOQ)!
At the end of the day each group will present their findings; the team with the most interesting and creative analysis will be awarded a prize. Afterwards, we’ll celebrate our achievements and continue the discussion over drinks.
We welcome participants from any and all backgrounds. If you have no programming skills and/or have not analysed social media data before, don’t worry—there will be plenty of opportunities for you to contribute, and data experts will be on hand to help.
If you would like to attend the event, please register on Eventbrite by Tuesday 10 January: https://tinyurl.com/SocialHumanitiesDatahack.
If you have any questions please email us at firstname.lastname@example.org. There is limited space so we recommend that you RSVP as early as possible!
10.00-10.30: Introduction and overview of the day
10.30-12.30: Workshops led by Mike Thelwall (SentiStrength), Taha Yasseri (topic modelling and Wikipedia), Jason Nurse (identity manifestation), Peter Fairfax (Brandwatch)
12.30-13.30: Team formation and working lunch
13.30-17.00: Data analysis (tea and coffee provided at 15.00)
17.00-18.00: Presentation of findings and group discussion
18.00-19.00: Prizes and drinks reception
Contact name: Yin Yin Lu
Contact email: email@example.com
Website: Registration with Eventbrite
Audience: Open to all