123 citations · 293 across the 7 of their papers we have counts for
7 papers · 1 filter
LibertyMFD: A Lexicon to Assess the Moral Foundation of Liberty
Oscar Araque, Lorenzo Gatti, Kyriaki Kalimeri
Quantifying the moral narratives expressed in the user-generated text, news, or public discourses is fundamental for understanding individuals' concerns and viewpoints and preventi…
MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction
Oscar Araque, Lorenzo Gatti, Kyriaki Kalimeri
Moral rhetoric plays a fundamental role in how we perceive and interpret the information we receive, greatly influencing our decision-making process. Especially when it comes to co…
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques
Oscar Araque, Lorenzo Gatti, Jacopo Staiano +1
Several lexica for sentiment analysis have been developed and made available in the NLP community. While most of these come with word polarity annotations (e.g. positive/negative),…
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
Youness Mansar, Lorenzo Gatti, Sira Ferradans +2
In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands. More specifically, our approach leverages affective lexica and word embeddi…
SentiWords: Deriving a High Precision and High Coverage Lexicon for Sentiment Analysis
Lorenzo Gatti, Marco Guerini, Marco Turchi
Deriving prior polarity lexica for sentiment analysis - where positive or negative scores are associated with words out of context - is a challenging task. Usually, a trade-off bet…
Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet
Marco Guerini, Lorenzo Gatti, Marco Turchi
Assigning a positive or negative score to a word out of context (i.e. a word's prior polarity) is a challenging task for sentiment analysis. In the literature, various approaches b…
Assessing Sentiment Strength in Words Prior Polarities
Lorenzo Gatti, Marco Guerini
Many approaches to sentiment analysis rely on lexica where words are tagged with their prior polarity - i.e. if a word out of context evokes something positive or something negativ…