Author Profiling in Social Media: The Impact of Emotions on Discourse Analysis

[EN] In this paper we summarise the content of the keynote that will be given at the 5th International Conference on Statistical Language and Speech Processing (SLSP) in Le Mans, France in October 23¿25, 2017. In the keynote we will address the importance of inferring demographic information for marketing and security reasons. The aim is to model how language is shared in gender and age groups taking into account its statistical usage. We will see how a shallow discourse analysis can be done on the basis of a graph-based representation in order to extract information such as how complicated the discourse is (i.e., how connected the graph is), how much interconnected grammatical categories are, how far a grammatical category is from others, how different grammatical categories are related to each other, how the discourse is modelled in different structural or stylistic units, what are the grammatical categories with the most central use in the discourse of a demographic group, what are the most common connectors in the linguistic structures used, etc. Moreover, we will see also the importance to consider emotions in the shallow discourse analysis and the impact that this has. We carried out some experiments for identifying gender and age, both in Spanish and in English, using PAN-AP-13 and PAN-PC-14 corpora, obtaining comparable results to the best performing systems of the PAN Lab at CLEF.The research work described in this paper was partially carried out in the framework of the SomEMBED project (TIN2015-71147-C2-1-P), funded by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO).Rosso, P.; Rangel-Pardo, FM. (2017). Author Profiling in Social Media: The Impact of Emotions on Discourse Analysis. Lecture Notes in Computer Science. 10583:3-18. doi:10.1007/978-3-319-68456-7_1S3181058