Title :
Visualization of spread of topic words on Twitter using stream graphs and relational graphs
Author :
Amma, Keigo ; Wada, Shunsuke ; Nakayama, Kanto ; Akamatsu, Yuki ; Yaguchi, Yuichi ; Naruse, Keitaro
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Aizu, Aizu-Wakamatsu, Japan
Abstract :
In this paper, we examine occurrences, cooccurrences, and characteristics for influence and meaning of words by visualizing large amounts of data from Twitter. We classified words using morphological analysis of tweets and developed a stream graph by finding the frequency of each word. We analyzed the co-occurrence of words using quantification methods of the fourth type to find relationships and showed distances between words in a similarity graph. We present examples of the relationships found by our analysis.
Keywords :
data visualisation; graph theory; social networking (online); Twitter; relational graphs; stream graphs; topic words visualization; Data visualization; Games; Image color analysis; Market research; Sports equipment; Time-frequency analysis; Twitter; Twitter analysis; relational graph; stacked graph; stream graph; visualization;
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
DOI :
10.1109/SCIS-ISIS.2014.7044759
