DOI | Resolve DOI: https://doi.org/10.3115/v1/N15-1078 |
---|
Author | Search for: Salameh, Mohammad; Search for: Mohammad, Saif1; Search for: Kiritchenko, Svetlana1 |
---|
Affiliation | - National Research Council of Canada. Information and Communication Technologies
|
---|
Format | Text, Article |
---|
Conference | 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, May 31–June 5, 2015, Denver, Colorado, USA |
---|
Abstract | When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. We show that sentiment analysis of English translations of Arabic texts produces competitive results, w.r.t. Arabic sentiment analysis. We discover that even though translation significantly reduces the human ability to recover sentiment, automatic sentiment systems are still able to capture sentiment information from the translations |
---|
Publication date | 2015-05-31 |
---|
Publisher | Association for Computational Linguistics |
---|
In | |
---|
Language | English |
---|
Peer reviewed | Yes |
---|
NPARC number | 23000028 |
---|
Export citation | Export as RIS |
---|
Report a correction | Report a correction (opens in a new tab) |
---|
Record identifier | b9431a3a-e900-4176-9f67-08ad6cd85cae |
---|
Record created | 2016-05-30 |
---|
Record modified | 2020-04-22 |
---|