Sentiment Analysis: Adjectives and Adverbs are Better than Adjectives Alone

By Paul Sabatier. International Conference on Web and Social Media, 2007

393 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/03086d1ea707933399c530299e6216237c415ef1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

A survey on opinion mining and sentiment analysis: Tasks, approaches and applications (2015, methodology): “[178] composed three Adverb-Adjective Combinations (AAC) scoring methods viz.”
Lexicon-Based Methods for Sentiment Analysis (2011, background): “tions, especially more recently, which have also included the use of adverbs (Benamara et al. 2007); adjectives and verbs (Kim and Hovy 2004); adjective phrases (Whitelaw, Garg, and Argamon 2005); two-word phrases (Turney 2002; Turney and Littman 2003);”
An Unsupervised Aspect-Sentiment Model for Online Reviews (2010, background): “So far, we focused on adjectives as sentiment indicators, however, there have been studies showing that other parts of speech can be very helpful for this task (e.g., Pang et al. 2002; Benamara et al. 2007).”
Sentiment Analysis: An Overview from Linguistics (2016, unknown): “…have increasingly noticed, however, that a great deal of sentiment is conveyed through other parts of speech, such as nouns (masterpiece, disaster), verbs (love, hate) or adverbs (skilfully, poorly), and phrases that contain those words (Benamara et al 2007, Subrahmanian & Reforgiato 2008).”
Twitter Sentiment Analysis (2015, background): “Benamara et al. proposed the Adverb-Adjective Combinations (AACs) approach that demonstrates the use of adverbs and adjectives to detect sentiment polarity (Benamara et al., 2007).”
Categorical and dimensional affect analysis in continuous input: Current trends and future directions (2013, background): “[61] or class combinations such as adjective–adverb [62] or adjective–verb–adverb [63], are best suited to reflect affect in text.”
Opinion Mining and Sentiment Analysis (2008, background): “There have been several targeted comparisons of the effectiveness of adjectives, verbs, and adverbs, where further subcategorization often plays a role [34, 221, 317].”
Ensemble of feature sets and classification algorithms for sentiment classification (2011, background): “Other researchers point out that adjectives and adverbs are better than adjectives alone and certain verbs and nouns are also strong indicators of sentiment [1,35].”
Current State of Text Sentiment Analysis from Opinion to Emotion Mining (2017, background): “Some previous works focus on comparing the effectiveness of adjectives, adverbs, verbs, and nouns in the classiﬁcation task, including Benamara et al. [2007], Nasukawa and Yi [2003], and Wiebe et al. [2004].”