Named Entity Recognition for social media data is challenging because of its inherent
noisiness. In addition to improper grammatical structures, it contains spelling inconsistencies …

Large scale data and predictive analytics are the most challenging tasks in the field of
academic data mining. Academic libraries are a great source of information and knowledge …

Optimal transport (OT) has emerged as a powerful framework to compare probability
measures, a fundamental task in many statistical and machine learning problems …

In the few works that have used NLP to study literary quality, sentiment and emotion analysis
have often been considered valuable sources of information. At the same time, the idea that …

Predicting literary quality and reader appreciation of narrative texts are highly complex
challenges in quantitative and computational literary studies due to the fluid definitions of …

Computational textual aesthetics aims at studying observable differences between aesthetic
categories of text. We use Approximate Entropy to measure the (un) predictability in two …

Literary novels are said to distinguish themselves from other novels through conventions
associated with literariness. We investigate the task of predicting the literariness of novels as …

Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow. An
author's dexterity in the use of these emotions captivates readers and makes it difficult for …

Studies on the growth of the Nigerian book publishing industry in the multimedia landscape
reiterate the need for the deployment of innovative marketing practices, given the observed …

Previous studies found that linguistic features can be used to predict the success of novels.
However, which specific linguistic features better contribute to a novel's popularity is unclear …