Title: Extraction and analysis of semantic proximity networks in the media coverage<\/strong> Keywords: Complex networks, Sociophysics, Digital humanities<\/p>\n Summary: Profile: Duration: 4 to 6 months between January and and June 2023
\nof a historical event<\/strong><\/p>\n
\nIn collaboration with Sophie Gebeil, MCF and researcher at the TELEMMe Laboratory
\n(CNRS UMR 7303), we offer an internship on the analysis of media coverage
\nof one historical event on the web, namely the 1983 \u201cMarche pour l\u2019\u00e9galit\u00e9 et contre
\nle racisme\u201d. The aim is to perform a semantic analysis of a corpus of web pages covering
\nthe event and its commemoration and to compute semantic proximity between
\nthe different pages. From these proximity measures we can then build a proximity
\nnetwork, which analysis will give insights about the structure of the media sphere
\naround this particular event, and about its evolution.
\nThe project is exploratory: the topic is new and the aim is to test methods for the
\nquantitative study of historical data. For this particular case, we combine tools from
\ncomputer science and network science to make sense of a rich corpus of online data.
\nThe project is interdisciplinary: the internship is paired with another internship
\nat the TELEMMe laboratory; work will involve close interactions with researchers
\nfrom social and historical sciences.<\/p>\n
\n\u2022 Master student in Physics, Complex systems, Computational social science.
\n\u2022 Good proficiency in Python.
\n\u2022 Some knowledge of HTML and semantic analysis would be useful.
\n\u2022 Interest in complex networks, digital humanities and interdisciplinary work is a
\nplus.<\/p>\n
\nApplication deadline: December 15, 2022
\nLocation: Centre de Physique Th\u00e9orique (CNRS UMR 7332), Marseille, France.
\nSupervision:
\nMathieu G\u00e9nois, Ma\u00eetre de Conf\u00e9rences AMU, Researcher at the CPT.
\nhttps:\/\/www.cpt.univ-mrs.fr\/~mgenois\/
\nContact: mathieu.genois@cpt.univ-mrs.fr<\/p>\n","protected":false},"excerpt":{"rendered":"