Titlebook: Generative Methods for Social Media Analysis; Stan Matwin,Aristides Milios,Fran?ois Théberge Book 2023 His Majesty the King in Right of Ca

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Jennifer Wilhelm,Ronald Wilhelm,Merryn Colea data. It fills a void, as the existing survey articles are either much narrower in their scope [7] or are dated [18, 220, 253]. We included two important aspects that currently gain importance in mining and modelling social media: dynamics and networks. Social dynamics are important for understand

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https://doi.org/10.1007/978-3-8349-8323-7ook, Twitter, and Instagram boast over two billion monthly active users, and as such, their ability to directly and indirectly connect the world‘s population has never been easier or more far reaching.

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https://doi.org/10.1007/978-3-030-80791-7ks to assess the potential dangers of increasingly more “effective” generative methods, as measured by how easy it is to distinguish the text generated from human-written texts. In light of the myriad of potential dangers relating to machine-generated text that is more and more humanlike, an overvie

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https://doi.org/10.1007/978-3-8349-8323-7ook, Twitter, and Instagram boast over two billion monthly active users, and as such, their ability to directly and indirectly connect the world‘s population has never been easier or more far reaching.

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HTML5 and Responsive Web Design,tline certain challenges relating to sentiment analysis as a whole that cause it to be a somewhat challenging problem, as well as challenges specific to social media platforms that make both topic and sentiment analysis more challenging than in the usual cases.

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Ontologies and Data Models for Cross-platform Social Media Data,ook, Twitter, and Instagram boast over two billion monthly active users, and as such, their ability to directly and indirectly connect the world‘s population has never been easier or more far reaching.

Rodent

Topic and Sentiment Modelling for Social Media,tline certain challenges relating to sentiment analysis as a whole that cause it to be a somewhat challenging problem, as well as challenges specific to social media platforms that make both topic and sentiment analysis more challenging than in the usual cases.

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Personal and Shared Experiential Concepts,Mining complex networks represented as graphs is now a well-established sub-field within data science. Analyzing social networks by investigating metadata as well as the content produced by the users can be powerful but it does not capture the dynamics and various types of interactions between users.