Using Arabic Microblogs Features in Determining Credibility
The increased usage of Twitter as a medium for reporting news and sharing information between people has caught the attention of researchers from different disciplines. One of the research directions is the analysis of online information from the ...
A Case Study for the Churn Prediction in Turksat Internet Service Subscription
Churn prediction is a customer relationship process that predicts for customers who are at the brink of transferring all the business to competitor. It is predicted by modeling customer behaviors in order to extract patterns. An acquaintance of a ...
Implementation of Chaotic Analysis on Retweet Time Series
Retweet has become one of the most prominent feature on social networks and an important mean for secondary content promotion. Most existing investigations of retweet behaviors on social networks are conducted based on empirical studies or information ...
The Good, the Bad and their Kins: Identifying Questions with Negative Scores in StackOverflow
A rapid increase in the number of questions posted on community question answering (CQA) forums is creating a need for automated methods of question quality moderation to improve the effectiveness of such forums in terms of response time and quality. ...
Mining Open and Crowdsourced Data to Improve Situational Awareness for Railway
This paper describes on-going research developing a system to harvest and utilise open and crowdsourced data related to the UK railway systems. This system will allow the controllers and decision makers to listen to the messages posted on social ...
Streaming Linear Regression on Spark MLlib and MOA
In recent years, analyzing data streams has attracted considerable attention in different fields of computer science. In this paper, two different frameworks, namely MOA and Spark MLlib, are examined for linear regression on streaming data. The focus is ...
Index Terms
- Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
ASONAM '23 | 145 | 53 | 37% |
ASONAM '21 | 118 | 22 | 19% |
ASONAM '19 | 286 | 41 | 14% |
Overall | 549 | 116 | 21% |