Predicting Article Sentiment Analysis Impact in Twitter: A Case Study in the Field of Information Sciences

T For a long time, the scholarly impact of a researcher has been evaluated by its citation count. But this method usually takes years to improve its impact rate. Twitter is one of the famous and rapidly growing microblogging platforms used in the context of “Altmetrics” as a solid alternative scale to identify quality research work. This research test whether Twitter sentiment is helpful to identify quality research work and there is a correlation between citation count and Altmetrics. We classified a small dataset of 6613 tweets into neutral, positive, and negative in information sciences. Our findings show that most of the sentiments of the tweets are neutral because of irrelevant discussion about the articles. Twitter comments do not provide important information about quality research papers except in exceptional cases. We cannot use tweets as a solid indicator to identify quality research work in the field of Information Sciences.