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The socialization of the web has undertaken a new dimension after theemergence of the Online Social Networks (OSN) concept. The fact that eachInternet user becomes a potential content creator entails managing a big amountof data. This paper explores the most popular professional OSN: LinkedIn. Ascraping technique was implemented to get around 5 Million public profiles. Theapplication of natural language processing techniques (NLP) to classify theeducational background and to cluster the professional background of thecollected profiles led us to provide some insights about this OSN's users andto evaluate the relationships between educational degrees and professionalcareers.

Scraping and Clustering Techniques for the Characterization of Linkedin Profiles