مشروع البحث: EXTRACTING BUSINESS PERFRMANCE SIGNALS FROM TWITTER NEWS
| dc.contributor.advisor | -WATT UNIVERSITY | |
| dc.date.accessioned | 2024-12-09T11:41:15Z | |
| dc.date.available | 2024-12-09T11:41:15Z | |
| dc.description | Additionally, we propose n-grams made from non-contiguous words as a novel feature to enhance performance in this context. Experiments involving a range of feature selection methods show that these new features provide valuable benefits in comparison with standard n-gram features | |
| dc.description.abstract | Social media and social networks underpin a revolution in communication between people, with the particular feature that much of that communication is open to all. This provides a massive pool of data that can be exploited by researchers for a wide variety of different applications. Data from Twitter is of particular interest in this sense, given its large global usage levels, and the availability of APIs and other tools that enable easy access to the publicly available stream of tweets. Owing to the wide public penetration of Twitter, many businesses make use of it to share their latest news, effectively using Twitter as a gateway to connect to end-users, consumers and/or investors. | |
| dc.identifier | 115 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/675 | |
| dc.subject | EXTRACTING BUSINESS PERFRMANCE SIGNALS FROM TWITTER NEWS | |
| dc.title | EXTRACTING BUSINESS PERFRMANCE SIGNALS FROM TWITTER NEWS | |
| dspace.entity.type | Project | |
| project.endDate | 2021 | |
| project.funder.name | الطب الحيوي | |
| project.investigator | ابرهيم دنقو | |
| project.startDate | 2020 |