  Understanding the current research trends, problems, and their innovative
solutions remains a bottleneck due to the ever-increasing volume of scientific
articles. In this paper, we propose NLPExplorer, a completely automatic portal
for indexing, searching, and visualizing Natural Language Processing (NLP)
research volume. NLPExplorer presents interesting insights from papers,
authors, venues, and topics. In contrast to previous topic modelling based
approaches, we manually curate five course-grained non-exclusive topical
categories namely Linguistic Target (Syntax, Discourse, etc.), Tasks (Tagging,
Summarization, etc.), Approaches (unsupervised, supervised, etc.), Languages
(English, Chinese,etc.) and Dataset types (news, clinical notes, etc.). Some of
the novel features include a list of young popular authors, popular URLs, and
datasets, a list of topically diverse papers and recent popular papers. Also,
it provides temporal statistics such as yearwise popularity of topics,
datasets, and seminal papers. To facilitate future research and system
development, we make all the processed datasets accessible through API calls.
The current system is available at http://lingo.iitgn.ac.in:5001/
