title: Linguistic markers of emotional state of the speech subject (on the problem of automatic monitoring of network communication texts)
metadata.name: dc.contributor.author
metadata.value: Mishlanov, Valerii A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Kadzhaya, Liudmila A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Kuznetsova, Yulia M.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2021-01-21T10:03:54Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2021-01-21T10:03:54Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2020-12
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Mishlanov, V. A., Kadzhaya, L. A., Kuznetsova, Yu. M. (2020). Linguistic markers of emotional state of the speech subject (on the problem of automatic monitoring of network communication texts). Media Linguistics, 7 (4), 428–444.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu22.2020.405
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/22572
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: This paper discusses linguistic and psychological aspects of the problem of automatic modusdictum
  analysis of texts published in social networks and other electronic media. Thereupon,
  theoretical questions are raised anew on the linguistic nature of modus, on the means to express
  “ego-meanings” in speech, on the differentiation of proper modus (autoreferential signs)
  and modal-evaluating predicates in dictum position, on the implicit methods of communicating
  modus information, and the resources to read this information based on discursive speech
  practices (conventional meanings). The applied goal of the paper is to provide “humanitarian”
  (psychological and linguistic) support for development of machine “mining” programs, i. e.
  automatic monitoring of network content and text identification with a certain subjective modality.
  To achieve this goal, we describe, in particular, such lexical-grammatical features of the
  texts that can be significant for determining psychological state of an individual or a professional
  group to identify certain public opinions. Conceptually, this research is connected with
  the idea of speech system which is manifested both at the level of styles and genres and within
  independent communicative units, as well as with one of the most important trends in the
  field of artificial intelligence — the method of relational-situational analysis of texts in natural
  language. Thematic groups of words (TGW) were compiled including “evaluation collocations”
  typical of those texts. The templates created on the basis of psychological and linguistic
  description model suggested in this paper can be used hereafter to develop algorithms for
  automatic monitoring of the network texts of a given theme (professional stability or mobility,
  professional crisis, etc.) and evaluation.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This work was financially supported by the Russian Foundation for Basic Research (grant
  no. 19-29-07163).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Media Linguistics;Volume 7; Issue 4
metadata.lang: -
metadata.name: dc.subject
metadata.value: dictum-modus automatic analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: thematic groups of words
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: network communication
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: professional crisis
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Linguistic markers of emotional state of the speech subject (on the problem of automatic monitoring of network communication texts)
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 428-444.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/22572/1/428-444.pdf
resources.format: Adobe PDF
resources.size: 713,49 kB