Name
Title | ||
|---|---|---|
Visualization of spread of topic words on Twitter using stream graphs and relational graphs |
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SCIS-ISIS.2014.7044759 | SCIS&ISIS |
Keywords | Field | DocType |
data visualisation,graph theory,social networking (online),twitter,relational graphs,stream graphs,topic words visualization,twitter analysis,relational graph,stacked graph,stream graph,visualization | Graph,Graph database,Information retrieval,Computer science,Visualization,Theoretical computer science,Artificial intelligence,Machine learning,Graph (abstract data type) | Conference |
ISSN | Citations | PageRank |
2377-6870 | 0 | 0.34 |
References | Authors | |
2 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| keigo amma | 1 | 0 | 0.34 |
| shunsuke wada | 2 | 0 | 0.34 |
| kanto nakayama | 3 | 0 | 0.34 |
| yuki akamatsu | 4 | 0 | 0.34 |
| Yuichi Yaguchi | 5 | 40 | 16.52 |
| Keitaro Naruse | 6 | 47 | 19.98 |