A Discourse Community or a Community of Practitioners is a group of people, an audience, who share common purposes/goals or interests and methods of communication (e.g., genres, jargon or professional terms of art, media/channels communication, citation systems).
A Discourse Community, a Community of Practitioners, shares values, beliefs, habits. They share information, data, knowledge, knowledge claims, information literacy perspectives, research methods.
Members of a Methodological Communities share research methods for developing and testing knowledge claims. They have common canonical texts (e.g., the community agrees certain texts are foundational. For instance, the Constitution of United States of America.
Just as people with similar religious beliefs, political loyalties, or cultural practices can be said to make up a community—even though they have never met—those who share similar assumptions about how to develop and test knowledge claims can be said to represent a Discourse Community or Community of Practice.
The terms Discourse Community and Community of Practice are fairly equivalent:
- The term Discourse Community was defined by John Sales in 1990 as “groups that have goals or purposes, and use communication to achieve these goals.”
- The term Community of Practice was initially coined in anthropology to describe how a group of people learn from one another (Jean and Etienne Wenger (1991).
Both terms are used to describe the language practices, purposes, ideologies, learning practices, and rituals of groups of people.
Both terms are fairly elastic:
- Discourse communities may be used, e.g., to describe Republicans or Democrats in the U.S. People who inhabit such broad communities may disagree on some things (e.g., fiscal policy), yet they still vote as a block because.
or
- Discourse communities could be used to more narrowly: a group of people with specific ideas about fiscal policy or immigration. To see how specific such communities can be, consider the following taxonomy from “Political discourse classification in social networks using context sensitive convolutional neural networks”:
