Identifying Implicit Links in CSCL Chats Using String Kernels and Neural Networks

Mihai Masala, Stefan Ruseti, Gabriel Gutu-Robu, Traian Rebedea, Mihai Dascalu, Stefan Trausan-Matu

Abstract: Chat conversations between more than two participants are often used in Computer Supported Collaborative Learning (CSCL) scenarios because they enhance collaborative knowledge sharing and sustain creativity. However, multi-participant chats are more difficult to follow and analyze due to the complex ways in which different discussion threads and topics can interact. This paper introduces a novel method based on neural networks for detecting implicit links that uses features computed with string kernels and word embeddings. In contrast to previous experiments with an accuracy of 33%, we obtained a considerable increase to 44% for the same dataset. Our method represents an alternative to more complex deep neural networks that cannot be properly used due to overfitting on limited training data.