Name
Abstract | ||
|---|---|---|
Social Networks Analysis has become a common trend among scholars and researchers worldwide. A great number of companies, institutions and organisations are interested in social networks data mining. Information published on many social networks, like Facebook, Twitter or Instagram constitute an important asset in many application fields, overall sentiment analysis, but also economics analysis, politics analysis and so on. Social networks analysis comprehends many disciplines and involves the application of different methodologies and techniques to define the criteria for generating the analytics, according to the purpose of the study. In this work, we focused on the semantic analysis of the content of textual information obtained from social media, aiming at extracting hot topics from social networks. We considered, as case study, reviews from the Yelp social network. The same methodology can be also applied for social and political opinion mining campaigns. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-98557-2_6 | ADVANCES IN INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS |
Field | DocType | Volume |
Data science,Data stream mining,Social media,Social network,Textual information,Sentiment analysis,Computer science,Computer network,Analytics,Politics | Conference | 23 |
ISSN | Citations | PageRank |
2367-4512 | 2 | 0.37 |
References | Authors | |
21 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Flora Amato | 1 | 458 | 66.48 |
| Giovanni Cozzolino | 2 | 3 | 15.60 |
| Francesco Moscato | 3 | 298 | 32.28 |
| Fatos Xhafa | 4 | 3433 | 343.33 |