<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Crestani, Fabio</dc:contributor>
  <dc:creator>Ríssola, Esteban A.</dc:creator>
  <dc:date>2021-09-09</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">Advances on psycho-linguistics have evidenced that the ways in which people use words could act as a reliable source to assess a wide array of behaviours.  Language use acts as an indicator of the individuals’ current mental state, personality and even personal values. In this thesis, we focus on language analysis to  study two closely related processes which encompass integral components of persons’ psychological profiles: mental health state and personality. Mental health state  assessment by analysing online user-generated content is a field that has recently attracted considerable attention. We start this dissertation by analysing the online  digital traces left by individuals in order to ascertain their mental state condition at a particular point in time. To this aim, we exploit the latent semantic structure of  social media users posts to spot early traces of depression. Next, present a weak-supervision framework to derive large quantities of data for the study of depression  on online settings. Moreover, we conduct a series of analytical studies aimed at gaining insights and extending the current knowledge on how mental disorders are  manifested through language and online behaviour in order to be able to detect the early onset of such disorders. While the mental state condition of individuals may  fluctuate over their lives, there is a core set of patterns concerning thought, affect and behaviour which is consistent across time and context, constituting the basis of  what is commonly referred to as personality. In the second part of this dissertation, we focus on the computational assessment of personality from language cues. We  present a novel approach to personality recognition in conversations based on capsule neural networks and exploit its inherent interpretability potential to gain  insights from its inner functioning. Moreover, we propose a novel open-vocabulary approach based on multiword expressions which aims at discovering distinctive  linguistic patterns of a personality trait. Such technologies will open new avenues to building more empathetic and naturalistic conversational systems.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://susi.usi.ch/global/documents/319225</dc:identifier>
  <dc:identifier>https://localhost:5000/ark:/12658/srd1319225</dc:identifier>
  <dc:identifier>https://susi.usi.ch/documents/319225/files/2021INFO009.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:rero-006-119509</dc:relation>
  <dc:relation>info:eu-repo/semantics/altIdentifier/ark/12658/srd1319225</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:subject xmlns:ns1="xml" ns1:lang="en">Information retrieval</dc:subject>
  <dc:subject xmlns:ns2="xml" ns2:lang="en">Natural language processing</dc:subject>
  <dc:subject xmlns:ns3="xml" ns3:lang="en">Social media analysis</dc:subject>
  <dc:subject xmlns:ns4="xml" ns4:lang="en">Text mining</dc:subject>
  <dc:subject xmlns:ns5="xml" ns5:lang="en">Data stream mining</dc:subject>
  <dc:subject xmlns:ns6="xml" ns6:lang="en">Data analysis</dc:subject>
  <dc:subject xmlns:ns7="xml" ns7:lang="en">Data visualisation</dc:subject>
  <dc:subject xmlns:ns8="xml" ns8:lang="en">Data science</dc:subject>
  <dc:subject xmlns:ns9="xml" ns9:lang="en">Healthcare informatics</dc:subject>
  <dc:subject xmlns:ns10="xml" ns10:lang="en">Machine learning</dc:subject>
  <dc:subject xmlns:ns11="xml" ns11:lang="en">Capsule neural networks</dc:subject>
  <dc:subject xmlns:ns12="xml" ns12:lang="en">Applied computing</dc:subject>
  <dc:subject xmlns:ns13="xml" ns13:lang="en">Depression assessment</dc:subject>
  <dc:subject xmlns:ns14="xml" ns14:lang="en">Personality assessment</dc:subject>
  <dc:subject>info:eu-repo/classification/udc/004</dc:subject>
  <dc:title xmlns:ns15="xml" ns15:lang="en">Text mining for online mental health state and personality assessment</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_db06</dc:type>
</oai_dc:dc>
