This paper proposes a text-analytics framework that integrates aspect-level sentiment
analysis (ASLSA) with bias-corrected least square dummy variable (LSDVc)–a panel data …

This paper employed information retrieval and statistical techniques for producing
systematic literature review (SLR). Sentiment analysis (SA) and opinion mining (OM) in …

The paper presents a text analytics framework that analyses online reviews to explore how
consumer-perceived negativity corresponding to the supply chain propagates over time and …

Purpose This research proposes a text analytics–based framework that examines the utility
of online customer reviews in evaluating automobile manufacturers and discovering their …

Identifying drivers of climate misinformation on social media is crucial to climate action.
Misinformation comes in various forms; however, subtler strategies, such as emphasizing …

We present a major step towards the creation of the first high-coverage lexicon of polarity
shifters. In this work, we bootstrap a lexicon of verbs by exploiting various linguistic features …

We present Lingmotif-lex, a new, wide-coverage, domain-neutral lexicon for sentiment
analysis in English. We describe the creation process of this resource, its assumptions …

Sentiment shifters, as a set of words and expressions that can affect text polarity, play a
fundamental role in opinion mining. However, the limited ability of current automated opinion …

This registered study aimed at testing the role of emotion in the intervention effect of an
experimental intervention study in academic settings. Previous analyses of the National …

Present research proposes a framework that integrates aspect-level sentiment analysis with
multi-criteria decision making (TOPSIS) and control charts to uncover hidden quality …