Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time andefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based onlinguistic cues that allows us to automatically discover, extract and label subjective adjectivesthat should be collected in a domain-based polarity lexicon. For this purpose, we designed abootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iterativelyidentify, extract and annotate positive and negative adjectives. Additionally, the methodautomatically creates lists of highly subjective elements that change their prior polarity evenwithin the same domain. The algorithm proposed reached a precision of 97.5% for positiveadjectives and 71.4% for negative ones in the semantic orientation identification task.

Spontaneous aggregation and global polar ordering in squirmer suspensions

We have developed numerical simulations of three dimensional suspensions of active particles to characterize the capabilities of the hydrodynamic stresses induced by active swimmers to promote global order and emergent structures in active suspensions. We have considered squirmer suspensions embedded in a fluid modeled under a Lattice Boltzmann scheme. We have found that active stresses play a central role to decorrelate the collective motion of squirmers and that contractile squirmers develop significant aggregates.