Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = word sequence disambiguation (WSD)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
15 pages, 1825 KiB  
Article
Machine Learning-Based Sentiment Analysis for Twitter Accounts
by Ali Hasan, Sana Moin, Ahmad Karim and Shahaboddin Shamshirband
Math. Comput. Appl. 2018, 23(1), 11; https://doi.org/10.3390/mca23010011 - 27 Feb 2018
Cited by 224 | Viewed by 39305
Abstract
Growth in the area of opinion mining and sentiment analysis has been rapid and aims to explore the opinions or text present on different platforms of social media through machine-learning techniques with sentiment, subjectivity analysis or polarity calculations. Despite the use of various [...] Read more.
Growth in the area of opinion mining and sentiment analysis has been rapid and aims to explore the opinions or text present on different platforms of social media through machine-learning techniques with sentiment, subjectivity analysis or polarity calculations. Despite the use of various machine-learning techniques and tools for sentiment analysis during elections, there is a dire need for a state-of-the-art approach. To deal with these challenges, the contribution of this paper includes the adoption of a hybrid approach that involves a sentiment analyzer that includes machine learning. Moreover, this paper also provides a comparison of techniques of sentiment analysis in the analysis of political views by applying supervised machine-learning algorithms such as Naïve Bayes and support vector machines (SVM). Full article
(This article belongs to the Special Issue Applied Modern Mathematics in Complex Networks)
Show Figures

Figure 1

Back to TopTop