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The file organizes a large collection of entries (about 57,000) into labeled records suitable for natural language processing tasks such as text classification, feature analysis, and model training. 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Dataset Overview\n## Labeling Scope\n## Negation Word Focus\n## Dataset Size and Usage","[{\"question\":\"What does the dataset focus on?\",\"answer\":\"It focuses on English tweet text related to depression, specifically the role of negation wording.\"},{\"question\":\"How is the dataset organized?\",\"answer\":\"It is organized into multi-labeled entries so each tweet record can be used for supervised NLP tasks.\"},{\"question\":\"What tasks can the dataset support?\",\"answer\":\"It can support text classification, feature analysis of negation cues, and training or evaluation of NLP models.\"}]","MultiLabeled Depression English 57000 Tweet negation words | XLSX"]