In this paper we present an investigation of the emotional content conveyed by words in online conversations captured on Twitter. A multivariate technique applied to co-occurence of words together with Correspondence Analysis is adopted in order to find clusters of meaningful words detecting emotional categories that provide meaning to everyday events. Specifically, given the current historical period, where the European Union has to gain trust in its citizens, a corpus of 155000 tweets selected through the Italian keywords ”Europa” and ”EU” is analyzed. Results show clearly how the textual content is structured according to the different emotional expressions. Abstract In questo articolo `e presentata un’analisi testuale che esplora il co...
Using existing natural language and sentiment analysis techniques, this study explores different dim...
NLP techniques can enrich unstructured textual data, detecting topics of interest and emotions. The ...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
With the proliferation of social media, textual emotion analysis is becoming increasingly important....
The aim of this study is to identify how Italian people talk about Brexit on Twitter, through a text...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
The growth and popularity of social media platforms have generated a new social interaction environm...
In this work we introduce an innovative approach for “Sentiment Analysis” or Opinion Mining, that is...
The growth and popularity of social media platforms have generated a new social interaction environm...
The paper aims to analyze the political language adopted on Twitter by the main Italian parties’ lea...
Using existing natural language and sentiment analysis techniques, this study explores different dim...
NLP techniques can enrich unstructured textual data, detecting topics of interest and emotions. The ...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
This study aims at analysing sentiments and emotions expressed by Twitter users at the onset of the ...
With the proliferation of social media, textual emotion analysis is becoming increasingly important....
The aim of this study is to identify how Italian people talk about Brexit on Twitter, through a text...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
Social networks are perceived by users as a natural environment for publicly sharing their thoughts ...
The growth and popularity of social media platforms have generated a new social interaction environm...
In this work we introduce an innovative approach for “Sentiment Analysis” or Opinion Mining, that is...
The growth and popularity of social media platforms have generated a new social interaction environm...
The paper aims to analyze the political language adopted on Twitter by the main Italian parties’ lea...
Using existing natural language and sentiment analysis techniques, this study explores different dim...
NLP techniques can enrich unstructured textual data, detecting topics of interest and emotions. The ...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...