Sentiment Analysis and Opinion Mining: A Survey
By Suad Alhojely. 2016
641 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/1ec569a1d5185193f6bce1b518f58b7af22a2adc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Louis-philippe Morency
- Amir Zadeh
- Soujanya Poria
- Percy Liang
- Erik Cambria
- Devamanyu Hazarika
- Rowan Zellers
- Eli Pincus
In Information Systems
- Louis-philippe Morency
- Amir Zadeh
- Hossein Hassani
- Juan Domingo Velásquez
- Maedeh Taj Mazinani
- Stephane Unger
- Jorge A. Balazs
- Christina Beneki
Citations in the corpus
- A survey of sentiment analysis in social media (2018, background): “[131] presented a short survey that covers the techniques and challenges appeared in the field of sentiment analysis.”
- MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos (2016, positive): “Text based sentiment analysis Research in text based sentiment analysis has been an active and extremely successful field (Pang and Lee, 2004, Vinodhini et.al., 2012).”
- Opinion Mining and Information Fusion: A survey (2016, background): “…the task of identifying positive and negative opinions, emotions and evaluations " [16], " the task of finding the opinions of authors about specific entities " [5], " tracking the mood of the public about a particular product or topic " [17], or simply " the task of polarity classification " [18].”
- Text Mining in Big Data Analytics (2020, methodology): “According to Vinodhini and Chandrasekaran [52], SVMs separate the classes by building a margin in an effort to minimize the distance between each class and that margin.”