Talk on “Bridging big data and qualitative methods in the social sciences”

Date: Jan 3rd 2018

Time: 2:15 PM

Location: TBD

Abstract: With the rise of social media, a vast amount of new primary research material has become available to social scientists, but the sheer volume and variety of this make it difficult to access through the traditional approaches: close reading and nuanced interpretations of manual qualitative coding and analysis. This work sets out to bridge the gap by developing semi-automated replacements for manual coding through a mixture of crowdsourcing and machine learning, seeded by the development of a careful manual coding scheme from a small sample of data. To show the promise of this approach, we attempt to create a nuanced categorisation of responses on Twitter to several cases of extreme circumstances.

 

Bio of speaker:

Dima is a Senior Data Scientist at Skyscanner where his focus is on developing and optimizing the Skyscanner’s travel search engine. Prior to Skyscanner, Dima was with King’s College London where he worked on analysis of BBC iPlayer (a joint project with BBC) and various social media websites (Twitter, Pinterest, Foursquare, etc.). He contributes to the data mining (KDD, WWW, etc.) and computer networks communities (Infocom, ComMag, etc.) and have his works featured by New ScientistBBC News and other media outlets. Dima has also co-founded and was a former CEO of Stanfy.com. More information – https://karamshuk.github.io/.

About

Raksha P.S. Raksha is a PhD Student at Web Science Lab. She has a Master’s degree in Web Technology from PES Institute Of Technology, Bangalore and Bachelor’s degree in Computer Science from K S Institute Of Technology, Bangalore. Prior to joining IIITB she has worked as a Big Data Engineer at Cogknit Semantics Pvt Ltd, Bangalore. Previously she has worked on Ontology Based Semantic Data Validation, Big Data, Data Visualization using D3.js, Web Crawlers and Developing Learning Management System Currently she is working on the IIITB Web Observatory Her areas of interests include Semantic Web Information retrieval, Data Analytics, Ontological Engineering and Web Science.