RIVA : A Real-Time Information Visualization and analysis platform for social media sentiment trend
Yong-Ting Wu, He‐Yen Hsieh, Xanno Kharis Sigalingging, Kuan‐Wu Su, Jenq‐Shiou Leu · 2017
In the social network, thousands of people produce data at the same time, and a huge amount of data will be produced in seconds. In addition, the number of users in the social network is increasing rapidly, and the data growth is expanding faster than before. To make good use of these data, in this paper we propose a Real-time Information Visualization and Analysis framework - RIVA to collect data from the social network, such as Twitter, by using Spark cloud computing platform to discover popular topics around the world. We also conduct the sentiment analysis to get people's sentiment for each issue and show the positive and negative sentiment distributions. Moreover, we fetch web news titles to check if they are consistent with the results from social network data analysis. Our experimental results show RIVA can process data in real-time, obtain and visualize information according to heterogeneous sources immediately.