Concept

Multimodal sentiment analysis

Publications associées (68)

Twitter Sentiment Analysis (Almost) from Scratch

Rémi Philippe Lebret, Ronan Collobert, Pedro Henrique Oliveira Pinheiro

A popular application in Natural Language Processing (NLP) is the Sentiment Analysis (SA), i.e., the task of extracting contextual polarity from a given text. The social network Twitter provides an immense amount of text (called tweets) generated by users ...

Idiap2016

Data Summarization with Social Contexts

Karl Aberer, Tian Guo, Rameez Rahman, Hao Zhuang, Xia Hu

While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...

Assoc Computing Machinery2016

Sentiment Classification of Tweets using Hierarchical Classification

Afroze Ibrahim Baqapuri

This paper addresses the problem of sentiment classification of short messages on microblogging platforms. We apply machine learning and pattern recognition techniques to design and implement a classification system for microblog messages assigning them in ...

Ieee2016

N-gram-Based Low-Dimensional Representation for Document Classification

Rémi Philippe Lebret, Ronan Collobert

The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent D ...

2015

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

EmotionWatch: Visualizing Fine-Grained Emotions in Event-Related Tweets

Pearl Pu Faltings, Claudiu-Cristian Musat, Valentina Sintsova, Renato Kempter

Spectators are increasingly using social platforms to express their opinions and share their emotions during big public events. Those reactions reveal the subjective perception of the event and extend its understanding. This has motivated us to develop a s ...

2014

EmotionWatch: Visualizing Fine-Grained Emotions in Event-Related Tweets

Pearl Pu Faltings, Claudiu-Cristian Musat, Valentina Sintsova, Renato Kempter

2014

Targeting HIV-related Medication Side Effects and Sentiment Using Twitter Data

Marcel Salathé

We present a descriptive analysis of Twitter data. Our study focuses on extracting the main side effects associated with HIV treatments. The crux of our work was the identification of personal tweets referring to HIV. We summarize our results in an infogra ...

2014

A Model of Online Social Interactions based on Sentiment Analysis and Content Similarity

Boi Faltings, Claudiu-Cristian Musat, Philippe Henri Jean Roussille

In this paper we create a model of human behavior in online communities, based on the network topology and on the communication content. The model contains eleven distinct hypotheses, which validate three intuitions. The rst intuition is that the network t ...

2013

Sentiment Analysis of User Comments for One-Class Collaborative Filtering over TED Talks

Andrei Popescu-Belis, Nikolaos Pappas

User-generated texts such as reviews, comments or discussions are valuable indicators of users’ preferences. Unlike previous works which focus on labeled data from user-contributed reviews, we focus here on user comments which are not accompanied by pre-de ...

ACM2013

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search