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Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.
The Influence And Deception Of Twitter: The Authenticity Of The Narrative And Slacktivism In The Australian Electoral Process, Benjamin Waugh, Maldini Abdipanah, Omid Hashemi, Shaquille A. Rahman, David M. Cook
The Influence And Deception Of Twitter: The Authenticity Of The Narrative And Slacktivism In The Australian Electoral Process, Benjamin Waugh, Maldini Abdipanah, Omid Hashemi, Shaquille A. Rahman, David M. Cook
Dr. David M Cook
It is uncertain how many discreet users occupy the social media community. Fake tweets, sock puppets, force‐multipliers and botnets have become embedded within the fabric of new media in sufficient numbers that social media support by means of quantity is no longer a reliable metric for determining authority and influence within openly expressed issues and causes. Election campaigns, and their associated political agendas, can now be influenced by non‐specific virtual presences that cajole and redirect opinions without declaring identity or allegiance. In the lead up to the 2013 Australian Federal Election, the open source Twitter activity for the two major …