Data Science – Automated Data Scraping with Python
Date: 5 November 2022
Time: 10 am
Workshop Language: English
Instructors: Mehmet Fuat Kına
This workshop is prepared to familiarize participants to automated data scraping with Python programming language. It is held on November 5, 2022, and designed in Turkish within the scope of Mimar Sinan University Sociology Conference (https://www.msgsusosolojikonferansi.com/). After a general introduction to the field of Data Science, the presentation outlines two types of data extraction techniques. These are respectively using Twitter API (“tweepy” library in Python) and HTML source codes of websites (“scrapy” library in Python). The content of the workshop is accessible at the following link: https://github.com/fuatkina/Veri-Bilimi-Otomatik-Veri-Cekme-Python. While the notebook named “Tweepy” works with Twitter API, the “Scrapy” document shows how to introduce URLs, create xpaths, and extract and store the data of interest. The “Spider” sheet contains the code that performs the same web scraping operation faster using the “spider” class.
Fuat Kına has been a PhD researcher at the Sociology Department of Koç University since 2018, working in three projects: Emerging Markets Welfare, Social ComQuant, and Politus. He has provided methodological support for the research papers and research design problems and performed various tasks related to computational social science and quantitative research. He recently started to serve as the instructor of the “Advanced Data Analysis with Python” course in the Computational Social Science MA program. He graduated from Boğaziçi University with a Bachelor of Economics (2015) and received his master’s degree with a statistical analysis on the relationship between anti-immigrant attitudes and labor precarity in Europe from İstanbul Şehir University (2018). Using advanced-level quantitative techniques of causal inference, he is currently working on the relationship between social movements, movement claims, and social welfare provisions. Some of his research interests are computational social science, social movements, social policy, statistics, and causal inference.