Automatic Social Media Data Extraction

نویسندگان

  • Estelle Xin Ying Kee
  • Jer Lang Hong
چکیده

Opinions, the key influencer of human behavior and activity is ranked as of one of the strong factors that determine the effectiveness of one’s strategy and approach in terms of influential power and trend setting capabilities. This highlights the importance of sentiment analysis done upon the extracted data. Today, statistics have shown significantly that most opinions can be obtained via many social media platforms. Social media has provided a convenient platform for web users to comfortably share their thoughts and to boldly voice up. Having to process such huge amount of data, it is proposed that automated sentiment analysis is done when extracting social media data. Using an effective algorithm which produces meaningful information from raw data, the possibilities of venturing deeper into areas like decision making and influential thinking are simply limitless.

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تاریخ انتشار 2016