# Optimization Of Cross Domain Sentiment Analysis Using Sentiwordnet

Source: [Optimization Of Cross Domain Sentiment Analysis Using Sentiwordnet](<https://www.sota2.com/research/paper/68fa61311e209131ce9f323a>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:29.253Z

Authors: K Paramesha, K C Ravishankar

Published: 2013-10-08T13:48:02.000Z

## Abstract

The task of sentiment analysis of reviews is carried out using manually built / automatically generated lexicon resources of their own with which terms are matched with lexicon to compute the term count for positive and negative polarity. On the other hand the Sentiwordnet, which is quite different from other lexicon resources that gives scores (weights) of the positive and negative polarity for each word. The polarity of a word namely positive, negative and neutral have the score ranging between 0 to 1 indicates the strength/weight of the word with that sentiment orientation. In this paper, we show that using the Sentiwordnet, how we could enhance the performance of the classification at both sentence and document level.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1401.3230>)

[PDF](<https://arxiv.org/pdf/1401.3230.pdf>)