IRCLNov 15, 2017

Sentiment analysis of twitter data

arXiv:1711.10377v21167 citations
Originality Synthesis-oriented
AI Analysis

This work addresses sentiment analysis for social media users, but it is incremental as it applies existing methods without introducing new techniques.

The paper tackled sentiment analysis on Twitter data by applying existing methods to various queries, revealing that neutral sentiments are significantly high, highlighting limitations in current approaches.

Social networks are the main resources to gather information about people's opinion and sentiments towards different topics as they spend hours daily on social media and share their opinion. In this technical paper, we show the application of sentimental analysis and how to connect to Twitter and run sentimental analysis queries. We run experiments on different queries from politics to humanity and show the interesting results. We realized that the neutral sentiments for tweets are significantly high which clearly shows the limitations of the current works.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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