![]() ![]() With the proliferation of blogs and social networks, opinion mining and sentiment analysis became a field of interest for many researches. ![]() In this conflict, it could help in engaging more people to help balancing the world’s public opinion, both during the fighting and after the cease fire. A deep sentiment analysis of social network data, such as Twitter, could lead to very interesting insights of global public opinion. Majority found Twitter to be a powerful means of expressing their activism against Israel’s brutal campaign in the region. This proves vital during the 2014 Israel – Gaza Conflict, with many taking to Twitter for real-time news and updates on the crisis. ![]() In other words, it determines whether a tweet is positive, negative or neutral. This project aims at qualifying and quantifying the trends in human emotions expressed by Twitter users over a period of time via sentiment analysis, which is the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. Computers cannot deal with implicit information as well as humans do. However, harnessing big data is challenging as data lacks structure and context. This represents a great source of data that we can analyse and derive valuable insights from. There are an estimated 200,000 Twitter users in Singapore. Singaporeans are also more connected to the Internet as compared to the rest of the world on average, with an Internet penetration rate is 73%, above the global average of 35%. According to a report by We Are Social, Twitter is growing the fastest in Asia Pacific and Singaporeans are one of the most active social media consumers in the world, with the world’s second highest social penetration rate in Singapore at 59%, more than double the global average of 26%. It has become a real-time information network generated by people around the world that let users share their thoughts about various topics in short updates or tweets in 140 characters of text or less. Twitter now boasts 284 million monthly active users and they send out 500 million tweets per day as of December 2014. Since Twitter launched in 2006, the social networking microblogging service has grown rapidly to become the second largest social network after Facebook. In the past decade, we have witnessed the rapid proliferation of social media worldwide. 12.4 Analyse Data on an Event/Topic Basis Rather Than on Time.12.3 Allowing the User to Tag Their Feelings to Their Status.12 Future Work / Improving the Effectiveness of Sentiment Analysis of Social Media Data.11.2 Misspelled Words and Abbreviations.11 Pitfalls of Using Conventional Text Analysis on Social Media Data.10 “Purified” English-only Training Data.7 Comparing the Performance of the 3 Classifiers.5.3 Setting up RapidMiner for Text Analysis.5.2.3 Numerous Support from Online Resources.5.2 Assessment of Appropriate Software for Text Analytics. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |