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  2. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    The problem is that most sentiment analysis algorithms use simple terms to express sentiment about a product or service. However, cultural factors, linguistic nuances, and differing contexts make it extremely difficult to turn a string of written text into a simple pro or con sentiment. [ 66 ]

  3. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Tweet data from 2009 including original text, time stamp, user and sentiment. Classified using distant supervision from presence of emoticon in tweet. 1,578,627 Tweets, comma, separated values Sentiment analysis 2009 [47] [48] A. Go et al. ASU Twitter Dataset Twitter network data, not actual tweets. Shows connections between a large number of ...

  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. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text.It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources."

  6. 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 ]

  7. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Edge-based: which use the edges and their types as the data source; Node-based: in which the main data sources are the nodes and their properties. Other measures calculate the similarity between ontological instances: Pairwise: measure functional similarity between two instances by combining the semantic similarities of the concepts they represent

  8. Social network analysis - Wikipedia

    en.wikipedia.org/wiki/Social_network_analysis

    Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. [1] It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties , edges , or links (relationships or interactions) that connect them.

  9. Outline of natural language processing - Wikipedia

    en.wikipedia.org/wiki/Outline_of_natural...

    Conversation analysis (CA) – approach to the study of social interaction, embracing both verbal and non-verbal conduct, in situations of everyday life. Turn-taking is one aspect of language use that is studied by CA. Discourse analysis – various approaches to analyzing written, vocal, or sign language use or any significant semiotic event.