How does computational discourse analysis help develop language policies?

1 What is language policy?

Language policy is a set of decisions and actions that affect the status, use, and diversity of languages in a given society. Language policy can be explicit or implicit, formal or informal, and can have various goals and impacts, such as promoting or suppressing certain languages, fostering or hindering multilingualism, or supporting or marginalizing certain groups of speakers. Language policy can also influence various domains and levels of language use, such as education, media, law, or identity.

2 Why is CDA relevant for language policy?

CDA can help you analyze how language policy is constructed, communicated, and contested through different types of discourse. For example, you can use CDA to examine how language policy documents, speeches, or campaigns use certain linguistic strategies, such as framing, persuasion, or legitimization, to convey their goals and values, or to address their audiences and stakeholders. You can also use CDA to investigate how language policy affects or reflects the discourse practices and patterns of different speakers and communities, such as their language choices, styles, or ideologies.

3 How can you use CDA tools and techniques?

CDA can benefit from various computational tools and techniques that can help you collect, process, and analyze large and diverse datasets of discourse. For example, you can use web scraping, text mining, or natural language processing to extract relevant information from online sources, such as news articles, social media posts, or blogs. You can also use corpus analysis, sentiment analysis, or topic modeling to identify and compare the linguistic features, patterns, and themes of different discourse genres, domains, or groups. You can also use visualization, network analysis, or machine learning to explore and interpret the relationships, structures, and trends of discourse data.

4 What are some examples of CDA applications for language policy?

CDA has been applied to various language policy issues and contexts, such as the role of media discourse in influencing public opinion about language policy initiatives like language revitalization, testing, or rights. It can also be used to analyze the impact of language policy on the linguistic diversity and vitality of endangered or minority languages, looking at the use of digital technologies, resources, or education to support or challenge language maintenance or shift. Additionally, CDA can be used to explore the influence of language policy on the linguistic identity and representation of different groups of speakers, including the use of varieties, code-switching, or multilingual practices to express or negotiate identity, belonging, or power.

5 What are some challenges and limitations of CDA for language policy?

CDA is not without its difficulties, such as the complexity and variability of discourse data, ethical and legal implications, and critical and reflexive interpretation. These issues may involve careful selection, annotation, and validation of data sources, methods, and tools; issues of consent, privacy, or copyright; and awareness of the assumptions, biases, or perspectives of the researchers, the tools, and the audiences.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?