University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Auteur Ahmed Hechaichi |
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Titre : How to analyze human sentiments : Covid19 pandemic Type de document : texte imprimé Auteurs : Ahmed Hechaichi, Auteur ; Mohamed Nadjib Mezerzi, Auteur ; Toumi,Lyazid, Directeur de thèse Année de publication : 2022 Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Sentiment analysis
Natural language processingIndex. décimale : 004 Informatique Résumé :
Sentiment analysis, or opinion mining, is the computer examination of people’s sentiments,
feelings, opinions, attitudes, moods, and emotions. It is one of the most active research
fields in natural language processing, data mining, information retrieval, and web mining.
Emotions and feelings have become more important in our daily lives in recent years. Many
people assume that sentiment analysis is just the process of determining whether a document
or a sentence reflects a positive or negative mood or opinion. It is, however, a far more
complicated issue. In both business and society, this interesting subject is becoming more
important.
In this master’s thesis, we define the sentiment analysis topic and related concepts across
the chapters, as well as the techniques used in preparing the collected dataset using nlp preprocessing
techniques. We suggested and analyzed multiple machine learning and deep learning
algorithms in order to categorize the tweets :naive bayes, support vector machine, logistic
regression,k-nearest neighbor, random forest,decision tree, long short term memory, convolutional
neural network ,hybrid of LSTM and CNN .
The best results of the accuracy we have achieved was 90.21% with LSTM model in
Corona_NLP dataset.Côte titre : MAI/0611 En ligne : https://drive.google.com/file/d/1QizJGrkJ6tYVOQm0lIwOjE_bnsMlzTxd/view?usp=share [...] Format de la ressource électronique : How to analyze human sentiments : Covid19 pandemic [texte imprimé] / Ahmed Hechaichi, Auteur ; Mohamed Nadjib Mezerzi, Auteur ; Toumi,Lyazid, Directeur de thèse . - 2022 . - ; 29cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Sentiment analysis
Natural language processingIndex. décimale : 004 Informatique Résumé :
Sentiment analysis, or opinion mining, is the computer examination of people’s sentiments,
feelings, opinions, attitudes, moods, and emotions. It is one of the most active research
fields in natural language processing, data mining, information retrieval, and web mining.
Emotions and feelings have become more important in our daily lives in recent years. Many
people assume that sentiment analysis is just the process of determining whether a document
or a sentence reflects a positive or negative mood or opinion. It is, however, a far more
complicated issue. In both business and society, this interesting subject is becoming more
important.
In this master’s thesis, we define the sentiment analysis topic and related concepts across
the chapters, as well as the techniques used in preparing the collected dataset using nlp preprocessing
techniques. We suggested and analyzed multiple machine learning and deep learning
algorithms in order to categorize the tweets :naive bayes, support vector machine, logistic
regression,k-nearest neighbor, random forest,decision tree, long short term memory, convolutional
neural network ,hybrid of LSTM and CNN .
The best results of the accuracy we have achieved was 90.21% with LSTM model in
Corona_NLP dataset.Côte titre : MAI/0611 En ligne : https://drive.google.com/file/d/1QizJGrkJ6tYVOQm0lIwOjE_bnsMlzTxd/view?usp=share [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0611 MAI/0611 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible