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The goal of Author Profiling (AP) is to identify demographic aspects (e.g., age, gender) from a given set of authors by analyzing their written texts. Recently, the AP task has gained interest in many problems related to computer forensics, psychology, marketing, but specially in those related with social media exploitation. As known, social media data is shared through a wide range of modalities (e.g., text, images and audio), representing valuable information to be exploited for extracting valuable insights from users. Nevertheless, most of the current work in AP using social media data has been devoted to analyze textual information only, and there are very few works that have started exploring the gender identification using visual information. Contrastingly, this paper focuses in exploiting the visual modality to perform both age and gender identification in social media, specifically in Twitter. Our goal is to evaluate the pertinence of using visual information in solving the AP task. Accordingly, we have extended the Twitter corpus from PAN 2014, incorporating posted images from all the users, making a distinction between tweeted and retweeted images. Performed experiments provide interesting evidence on the usefulness of visual information in comparison with traditional textual representations for the AP task.

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This work aims to generate classification models that help determine the colour of an epidemiological semaphore (ES) by analysing online news and being better prepared for the different changes in the evolution of the pandemic. To accomplish this, we introduce Cov-NES-Mex corpus, a collection of 77,983 news (labelled with the Mexican ES system) related to Covid-19 for the 32 regions of Mexico. Also, we showed measures that describe the corpus as imbalanced and with a high vocabulary overlap between classes. In addition, evaluation measurements of the pandemic by region are proposed. Furthermore, a classification model, based on a transformer architecture specialised for the Spanish language, achieved up to 0.83 of F-measure. Thus, this work provides evidence that there is essential information in the news that can be used to determine the colour of the ES up to 4 weeks in advance. Finally, the presented results could be applied to other Spanish-speaking countries, which do not have an ES system, thus inferring and comparing their situation concerning the Mexican ES.

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