Name
Abstract | ||
|---|---|---|
Social computing has been emerged in the era of computing where the technology is being used to share information, ask suggestions, create academic groups for discussions and to name a few. Due to vast number of users and massive usage, many data mining techniques are applied social web data for numerous purposes. This paper introduces a solution to extract and analyze comments of masters students from the Facebook academic group. The proposed technique is implemented using Facebook graph API to extract the comments and then those are classified into three groups (i.e. positive, negative and neutral) using Bayesian Network probabilistic model. The said system may help administration to improve the learning environment by providing different proformas and analyzing different opinions from the students. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/INTELLECT.2017.8277622 | 2017 First International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) |
Keywords | DocType | ISBN |
Social computing,Opinion analysis,Educational system,Probabilistic model | Conference | 978-1-5386-2970-3 |
Citations | PageRank | References |
1 | 0.38 | 5 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nisha Tanwani | 1 | 1 | 0.38 |
| Sandesh Kumar | 2 | 1 | 0.38 |
| Akhtar Hussain Jalbani | 3 | 1 | 0.38 |
| Saima Soomro | 4 | 1 | 0.38 |
| Muhammad Ibrahim Channa | 5 | 1 | 0.38 |
| Zeeshan Nizamani | 6 | 1 | 0.38 |