CLJul 10, 2018

Paired Comparison Sentiment Scores

arXiv:1807.03591v12 citations
Originality Synthesis-oriented
AI Analysis

This work provides a method for building sentiment lexicons, which is incremental as it adapts an existing psychological technique to natural language processing.

The authors applied the method of paired comparisons from psychology to create continuous sentiment scores for German words, resulting in an initial lexicon of 199 words and finding that about 18 comparisons are needed to estimate scores for new words.

The method of paired comparisons is an established method in psychology. In this article, it is applied to obtain continuous sentiment scores for words from comparisons made by test persons. We created an initial lexicon with $n=199$ German words from a two-fold all-pair comparison experiment with ten different test persons. From the probabilistic models taken into account, the logistic model showed the best agreement with the results of the comparison experiment. The initial lexicon can then be used in different ways. One is to create special purpose sentiment lexica through the addition of arbitrary words that are compared with some of the initial words by test persons. A cross-validation experiment suggests that only about 18 two-fold comparisons are necessary to estimate the score of a new, yet unknown word, provided these words are selected by a modification of a method by Silverstein & Farrell. Another application of the initial lexicon is the evaluation of automatically created corpus-based lexica. By such an evaluation, we compared the corpus-based lexica SentiWS, SenticNet, and SentiWordNet, of which SenticNet 4 performed best. This technical report is a corrected and extended version of a presentation made at the ICDM Sentire workshop in 2016.

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