Analysis and Correlation of Behaviour on Online Social Networks
Thesis type DATA ANALYSIS
Description Online social networks, such as Instagram and Facebook, allow users to interact and debate with each other. In this research, the candidate will collect large quantities of data from social networks and from public repositories such as Wikidata. The data will be organized and analyzed using big data techniques (such as Pyspark). Then, the student will characterize the behaviour of different classes of users on the social network (e.g., nationality, activity, language, age, etc.). The student will analyze possible bias in the categories and the dynamic of the changes. The student will possibly use machine learning techniques, forecasting methods and graphs.
Required skills Data analysis, python programing, preferentially big data (pyspark), machine learning, graphs
Notes Contact firstname.lastname@example.org
Deadline 20/04/2023 PROPONI LA TUA CANDIDATURA