Andere Kunden interessierten sich auch für
![Apprendre les émotions à l'aide de techniques automatisées de détection des affects]( "Apprendre les émotions à l'aide de techniques automatisées de détection des affects")
Apprendre les émotions à l'aide de techniques automatisées de détection des affects36,99 €![Hashtag Twitter]( "Hashtag Twitter")
Hashtag Twitter26,99 €![Sentiment Analysis On The Topic Of Fitness Using The OSN Twitter]( "Sentiment Analysis On The Topic Of Fitness Using The OSN Twitter")
Sentiment Analysis On The Topic Of Fitness Using The OSN Twitter23,99 €![Analysis of tweets and their influence in life insurance]( "Analysis of tweets and their influence in life insurance")
Analysis of tweets and their influence in life insurance36,99 €![Recapitulization of Tweets Using Graph-based Clustering]( "Recapitulization of Tweets Using Graph-based Clustering")
Recapitulization of Tweets Using Graph-based Clustering23,99 €![Twitter Spam Detection and Traffic Classification]( "Twitter Spam Detection and Traffic Classification")
Twitter Spam Detection and Traffic Classification29,99 €![SENTIMENT ANALYSIS ON TWITTER]( "SENTIMENT ANALYSIS ON TWITTER")
SENTIMENT ANALYSIS ON TWITTER29,99 €
In 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 hasbeen done so far. Using WordNet combined with the Plutchik affective model, a simple edge-based metric has thus been designed.