Python and Twitter to Analyze the Videogames Market

LEARNING TO USE CODING LANGUAGE TO UNDERSTAND, THROUGH THE ANALYSIS OF DATA ON TWITTER, HOW SOME BRANDS COULD ENTER THE EGAMES MARKET. THIS WAS THE TASK GIVEN TO STUDENTS BY NIELSEN SPORTS

Is it possible to conduct market analysis by collecting data on Twitter? Of course it is. This was demonstrated by the students of the Social Media Marketing course with their projects, developed in the last semester and presented during the last lesson in front of the managers of Nielsen Sports, a provider of analytics and insights within the sports industry, which gave students the task of analyzing the eGames market. "The objective was to understand how brands can enter the growing videogame market. Each group, through a market analysis carried out by collecting data on Twitter with the help of Python, tried to understand which videogames are more suitable with the brand equity of different brands: energy drinks, fast food chains, computers, banks, fashion, cars," explains Gaia Rubera, director of the new Master of Science in Data Science and Business Analytics and responsible for the course.

"For example, my team tried to understand which kind of videogames should be associated with certain computer brands. To do this, we analyzed and crossed the Twitter data of the various video games and computer brands," explains Alberto Maragno, a Marketing Management student. “Among other things, we analyzed the followers and the different tweets on which we carried out a sentiment analysis, which means investigating the opinions of users in order to measure their perception of brands”.

"Students not only realized that Twitter is a useful tool for market analysis, used by some companies, but they also had to face and somehow overcome the difficulty of analyzing huge data sets," adds the professor. All the students in fact used Python for the very first time – a coding language which, starting from the 2017-18 academic year, is taught in all Bocconi Bachelors. "This was the complicated and stimulating aspect of the project: dealing with completely new methods and learning the language of programming by applying it to big data for a concrete need", says Alberto.

by Benedetta Ciotto