As the number of users on social media rise, information creation and circulation increase day af... more As the number of users on social media rise, information creation and circulation increase day after day on a massive basis. People can share their ideas and opinions on these platforms. A social media microblogging site such as Facebook or Twitter is the favoured medium for debating any important event, and information is shared immediately. It causes rumours to spread quickly and circulates inaccurate information, making people uneasy. Thus, it is essential to evaluate and confirm the level of veracity of such information. Because of the complexities of the text, automated detection of rumours in their early phases is challenging. This research employs various NLP techniques to extract information from tweets and then applies various machine learning models to determine whether the information is a rumour. The classification is performed using three classifiers such as SVC (Support Vector Classifier), Gradient Boosting, and Naive Bayes classifiers for five different events from th...
International Journal of Advance Research, Ideas and Innovations in Technology, 2017
Accurately predicting student performance is useful in different contexts in universities. Educat... more Accurately predicting student performance is useful in different contexts in universities. Educational data mining (EDM) is an emerging discipline, concerned with various approaches such as predicting student performance, Analysis and data visualization, providing feedback for supporting instructors, recommendations for students and so on that automatically extracts meaning from large data generated by or related to people's learning activities in an educational setting. For example, identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. One of the biggest challenges is to improve the quality of the educational processes so as to enhance student’s performance. The results of these studies give insight into techniques for accurately predicting student performance.
As the number of users on social media rise, information creation and circulation increase day af... more As the number of users on social media rise, information creation and circulation increase day after day on a massive basis. People can share their ideas and opinions on these platforms. A social media microblogging site such as Facebook or Twitter is the favoured medium for debating any important event, and information is shared immediately. It causes rumours to spread quickly and circulates inaccurate information, making people uneasy. Thus, it is essential to evaluate and confirm the level of veracity of such information. Because of the complexities of the text, automated detection of rumours in their early phases is challenging. This research employs various NLP techniques to extract information from tweets and then applies various machine learning models to determine whether the information is a rumour. The classification is performed using three classifiers such as SVC (Support Vector Classifier), Gradient Boosting, and Naive Bayes classifiers for five different events from th...
International Journal of Advance Research, Ideas and Innovations in Technology, 2017
Accurately predicting student performance is useful in different contexts in universities. Educat... more Accurately predicting student performance is useful in different contexts in universities. Educational data mining (EDM) is an emerging discipline, concerned with various approaches such as predicting student performance, Analysis and data visualization, providing feedback for supporting instructors, recommendations for students and so on that automatically extracts meaning from large data generated by or related to people's learning activities in an educational setting. For example, identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. One of the biggest challenges is to improve the quality of the educational processes so as to enhance student’s performance. The results of these studies give insight into techniques for accurately predicting student performance.
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Papers by Manya Gidwani