{"product_id":"learning-emotions-using-automated-affect-sensing-techniques-plecrus-ai-von-thomas-belin","title":"Learning emotions using automated affect sensing techniques","description":"\u003cp\u003eIn a world progressively digitalised, it is arguable whether Humanity will one day need to be re-defined. If chemical processes, such as emotions, are one day understood by ¿digital beings¿, Humanity would probably enter the ¿Transisto-Sapiens¿ era. In this project, the focus is made on identifying feelings in texts. Extracted from Twitter, a social media allowing its community to answer the question: ¿what are you doing?¿ in 140 characters, these texts usually display a lack of grammatical structure. The classical approach considering tools such as a sentence parser or a POS tagger does not apply. Indeed, as low informational content is available, a too strict feature reduction policy would often result in no text at all. The interest is thus to evaluate the accuracy one can expect on a corpus not pre-processed at all. Focusing solely on surface features, a metric measuring the emotional content of a particular concept is required. To the best of the author¿s knowledge, none has been done so far. Using WordNet combined with the Plutchik affective model, a simple edge-based metric has thus been designed.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783659971327\"\u003e\u003ch3\u003ePlecrus AI\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Softcover - 9783659971327","offer_id":39430324224093,"sku":"9783659971327","price":55.9,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/a6f9a4bb-84f7-4f51-b0de-a68d598ba711.jpg?v=1773207997","url":"https:\/\/shop.autorenwelt.de\/products\/learning-emotions-using-automated-affect-sensing-techniques-plecrus-ai-von-thomas-belin","provider":"Autorenwelt Shop","version":"1.0","type":"link"}