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Discourse Analysis



NLP makes machine to understand human language but we are facing issues like word ambiguity, sarcastic sentiments analysis and many more. One of the issue is to predict correctly relation between words like "Patrick went to the club on last Friday. He met Richard." Here, 'He' refers to 'Patrick'. This kind of issue makes Discourse analysis one of the important applications of Natural Language Processing.

What is Discourse Analysis ?

The word discourse in linguistic terms means language in use. Discourse analysis may be defined as the process of performing text or language analysis, which involves text interpretation and knowing the social interactions. Discourse analysis may involve dealing with morphemes, n-grams, tenses, verbal aspects, page layouts, and so on. It is often used to refer to the analysis of conversations or verbal discourse. It is useful for performing tasks, like Anaphora Resolution (AR) , Named Entity Recognition (NER) etc.

Approaches to Discourse Analysis

Sociology: One of the concerns in sociology is to understand how social members
make sense of everyday life. It can be done by Analysing Conversations.
Sociolinguistics:
  • Ethnography understanding social context of linguistic interaction like "who says to whom and where"
  •  Interactional it concern with importance of context in production and interpretation of discourse. It not only concerned with grammatical features but also tune and rhythm of speech.

 Philosophy:
  •  Speech Act Theory It is a logico-philosophic perspective on conversational organization focusing on interpretation rather than the production of utterances in discourse. It grows from the basic belief that language is used to perform actions.
  • Pragmatics : This theory formulates conversational behaviour in terms of general “principles” rather than rules. At the base of pragmatic approach to conversation analysis is Grecian's co-operative principle. This principle is the broken down into specific maxims: Quantity (say only as much as necessary), Quality (try to make your contribution one that is true), Relation (be relevant), and manner (be brief and avoid ambiguity). 
Spoken and Written Discourse
There is huge difference between spoken English and written English. Spoken English is not grammatically correct whereas written is. Actually informal English i.e. casual conversation over chat with friend or relative etc counted as spoken . And  English spoken at job interview, public place or with boss(manager), written in articles counted as written English because these are generally grammatically correct. Formal and Informal English also create issue while analysing discourse. 


References :
[1] "Natural Language Processing and Text Mining" by Anne Kao and Stephen R. Poteet
[2] https://jumarohisnanto.wordpress.com/2012/04/20/approaches-to-discourse-analysis/
[3] https://www.slideshare.net/samira_sheytoona/discourse-analysis-schmitts-book-chapter-4
[4] https://www.upwork.com/hiring/for-clients/artificial-intelligence-and-natural-language-processing-in-big-data/

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