Textual Analysis §

Group: 4 #group-4

Relations §

• Text Simplification: Text simplification is the process of modifying texts to make them easier to read and understand, which involves textual analysis.
• Deconstruction: Deconstruction is a method of textual analysis and interpretation.
• Text Summarization: Text summarization is the process of creating a concise summary of a longer text, which is a common application of textual analysis.
• Computational Linguistics: Computational linguistics is the study of computational models of language, which can be applied to textual analysis tasks.
• Content Analysis: Content analysis is a method used in textual analysis to systematically analyze the content of texts.
• Text Classification: Text classification is the process of assigning predefined categories or labels to texts, which is a common task in textual analysis.
• Text Mining: Text mining is the process of extracting valuable information from large collections of texts, which is a key application of textual analysis.
• Deconstruction: Deconstruction is a method of textual analysis that questions the assumptions and hierarchies within texts.
• Text Clustering: Text clustering is the process of grouping similar texts together, which is a common task in textual analysis.
• Text Generation: Text generation is the process of automatically generating human-like texts, which involves understanding and modeling language through textual analysis.
• Information Retrieval: Information retrieval is the process of finding relevant information from large collections of texts, which is related to textual analysis.
• Sentiment Analysis: Sentiment analysis is the process of identifying and extracting subjective information from texts, which is a common task in textual analysis.
• Topic Modeling: Topic modeling is a method for discovering abstract topics that occur in a collection of texts, which is relevant to textual analysis.
• Machine Translation: Machine translation is the process of automatically translating texts from one language to another, which involves textual analysis.
• Natural Language Processing: Natural language processing is a field that deals with the computational analysis and generation of human language, which is relevant to textual analysis.
• Stylistics: Stylistics is the study of the ways in which meaning is constructed through language choices, which is relevant to textual analysis.
• Semiotics: Semiotics is the study of signs and symbols, which is relevant to the analysis of texts and their meanings.
• Text Augmentation: Text augmentation is the process of creating new texts by modifying existing ones, which involves textual analysis and generation.
• Discourse Analysis: Discourse analysis is a method used in textual analysis to study the use of language in social contexts.
• Hermeneutics: Hermeneutics is a theory and methodology of interpretation, especially the interpretation of texts, which is relevant to textual analysis.
• Corpus Linguistics: Corpus linguistics is the study of language data using large collections of texts, which can be used in textual analysis.