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Analyzing Social Media Through Natural Language Processing

The Centre for the Analysis of Social Media employs Natural Language Processing (NLP) to enable automatic language understanding of vast datasets. By integrating methodologies from mathematics, computer science, linguistics, and sociology, we create classifiers that categorize social media content, such as Tweets. This allows researchers to analyze public responses, exemplified by our work on the inquest of Mark Duggan. Our findings suggest classifiers excel in specific, contextual conversations but struggle with generic data. Improving iterative development in NLP is essential for better accuracy over time.

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Analyzing Social Media Through Natural Language Processing

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  1. CASM The Centre for the Analysis of Social Media

  2. Social network analysis Natural Language Processing

  3. Natural language processing The Classifier • Combines: Mathematics, computer science, linuistics, sociology • Allows: computer to automatically understand language • Is our: analytical window into datasets that are too large to be read • The practical value: of NLP is to create classifiers • Classifiers are models that are taught to put Tweets into categories defined by the analyst: SLUICE GATES

  4. Natural language processing Method 51

  5. duggan on twitter Understanding the public response to the inquest of Mark Duggan through Social Media

  6. Natural language processing How well do NLP Classifiers work? • Demos paper – ‘VoxDigitas’ – about to be released Work best when… Work worst when… Generic, not specific Trained on a specific conversation, especially events Longitudinal, over a long period of time Trained to make distinctions naturally present in the data (Grounded Theory Methodology) There is little iterative development with the data

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