Using eye-tracking data to create a weighted dictionary for sentiment analysis: the eye dictionary

Extracting information from written texts is of paramount importance to many entities (e.g. businesses, public organizations, individuals), but the exponential growth of available data has made this task beyond any single human being or business. Sentiment analysis is a tool to automatically transform the information extracted into knowledge. One of the main challenges is to assess if a text is positive or negative, which can be tackled using a dictionary where each word has a positive or negative associated value and then combining single-words values to express an overall text sentiment. In order to use such lexicon-based approach, we need an existing dictionary or to build a new one. In this work we present a new dictionary for sentiment analysis developed using eye-tracking data to determine the relevance of words and we assess its performances against other existing dictionaries

Model Selection and Simplification Using Lattices

This paper shows how to cope with a problem of model selection and simplification using the principle of coherence (Gabriel (1969): A procedure involving testing a set of models ought not accept a model while rejecting a more general model). The mathematical lattice theory is used to define a partial ordering over the space of considered models. Several examples of partial ordering in large families of models are given along with a searching algorithm to determine the best model with respect to chosen criteria.model selection and simplification; principle of coherence; lattice of models; regression; ARMA models

Model Selection and Simplification Using Lattices

This paper shows how to cope with a problem of model selection and simplification using the principle of coherence (Gabriel (1969): A procedure involving testing a set of models ought not accept a model while rejecting a more general model). The mathematical lattice theory is used to define a partial ordering over the space of considered models. Several examples of partial ordering in large families of models are given along with a searching algorithm to deter- mine the best model with respect to chosen criteria.Model selection and simplification, Principle of coherence, Lattice of models, Regression, ARMA models