This paper empirically studies the effects of representation choices on neural sentiment analysis for Modern Hebrew, a morphologically rich language (MRL) for which no sentiment analyzer currently exists. We study two dimensions of representational choices: (i) the granularity of the input signal (token-based vs. morpheme-based), and (ii) the level of encoding of vocabulary items (string-based vs. character-based). We hypothesise that for MRLs, languages where multiple meaning-bearing elements may be carried by a single space-delimited token, these choices will have measurable effects on task perfromance, and that these effects may vary for different architectural designs: fully-connected, convolutional or recurrent. Specifically, we hypothesize that morpheme-based representations will have advantages in terms of their generalization capacity and task accuracy, due to their better OOV coverage. To empirically study these effects, we develop a new sentiment analysis benchmark for Hebrew, based on 12K social media comments, and provide two instances thereof: token-based and morpheme-based. Our experiments show that the effect of representational choices vary with architectural types. While fully-connected and convolutional networks slightly prefer token-based settings, RNNs benefit from a morpheme-based representation, in accord with the hypothesis that explicit morphological information may help generalize. Our endeavor also delivers the first state-of-the-art broad-coverage sentiment analyzer for Hebrew, with over 89% accuracy, alongside an established benchmark to further study the effects of linguistic representation choices on neural networks’ task performance.
|Title of host publication||COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings|
|Editors||Emily M. Bender, Leon Derczynski, Pierre Isabelle|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||11|
|State||Published - 2018|
|Event||27th International Conference on Computational Linguistics, COLING 2018 - Santa Fe, United States|
Duration: 20 Aug 2018 → 26 Aug 2018
|Name||COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings|
|Conference||27th International Conference on Computational Linguistics, COLING 2018|
|Period||20/08/18 → 26/08/18|
Bibliographical noteFunding Information:
We thank Tzipy Lazar-Shoef for research assistance, and are thankful to three anonymous reviewers for their insightful comments. This research is funded by the Israel Science Foundation, ISF grant 1739/26, for which we are grateful.
© 2018 COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings. All rights reserved.