Year: 2014
Type: article
Abstract: Sentiment analysis on English texts is a highly popular and well-studied topic. On the other hand, the research in this field for morphologically rich languages is still in its infancy. Turkish is an agglutinative language with a very rich morphological structure. For the first time in the literature, this paper investigates and reports the impact of the natural language preprocessing layers on the sentiment analysis of Turkish social media texts. The experiments show that the sentiment analysis performance may be improved by nearly 5 percentage points yielding a success ratio of 78.83% on the used data set.
Source: DergiPark (Istanbul University)
Institutions: Istanbul Technical University, Turkcell (Turkey)
Language: Turkish
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2586769279