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  2. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

  3. Multimodal sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Multimodal_sentiment_analysis

    Multimodal sentiment analysis is a technology for traditional text-based sentiment analysis, which includes modalities such as audio and visual data. [1] It can be bimodal, which includes different combinations of two modalities, or trimodal, which incorporates three modalities. [ 2 ]

  4. Social media analytics - Wikipedia

    en.wikipedia.org/wiki/Social_media_analytics

    In other words, data analysis is the phase that takes filtered data as input and transforms that into information of value to the analysts. Many different types of analysis can be performed with social media data, including analysis of posts, sentiment, sentiment drivers, geography, demographics, etc. The data analysis step begins once we know ...

  5. Robert P. Schumaker - Wikipedia

    en.wikipedia.org/wiki/Robert_P._Schumaker

    Schumaker also works in the field of Sports Analytics authoring numerous papers on greyhound [7] and harness racing prediction [8] as well as using Twitter sentiment to predict Premier League [9] and NFL matches. [10] He has also authored a book on the subject, Sports Data Mining (2010; ISBN 978-1-4419-6729-9).

  6. WordStat - Wikipedia

    en.wikipedia.org/wiki/WordStat

    Topic modeling to extract the main themes using NNMF and Factor Analysis. Correspondence analysis in order to identify words or concepts (or content categories) associated with any categorical meta-data associated with documents. Pre-and post-processing with R and python script; Analyze more than 70 languages including Chinese, Japanese, Korean ...

  7. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Scientific researchers incorporate text mining approaches into efforts to organize large sets of text data (i.e., addressing the problem of unstructured data), to determine ideas communicated through text (e.g., sentiment analysis in social media [15] [16] [17]) and to support scientific discovery in fields such as the life sciences and ...

  8. Muck Rack Introduces Integrated Social Listening

    lite.aol.com/tech/story/0022/20250212/9356608.htm

    Analyze sentiment and engagement patterns to gauge audience reactions and refine messaging. Measure Impact with integrated social and earned media analytics to demonstrate campaign effectiveness. New Social Listening Templates and Widgets. Within Muck Rack Dashboards, Muck Rack is introducing two new Social Dashboard Templates.

  9. Social data analysis - Wikipedia

    en.wikipedia.org/wiki/Social_data_analysis

    When talking about social data analytics, there are a number of factors it's important to keep in mind (which we noted earlier): [1] Sophisticated Data Analysis: what distinguishes social data analytics from sentiment analysis is the depth of the analysis. Social data analysis takes into consideration a number of factors (context, content ...