# The Evolution of Sentiment Analysis - A Review of Research Topics, Venues, and Top Cited Papers

arXiv: https://arxiv.org/abs/1612.01556 · HTML: https://mlsanity.com/paper/1612.01556/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Dec 2016.

## Built on by (most cited first, 20 of 20)

- [Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions](https://mlsanity.com/paper/2403.01222/) (2024)
- [The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements](https://mlsanity.com/paper/2101.06053/) (2021)
- [Financial Sentiment Analysis on News and Reports Using Large Language Models and FinBERT](https://mlsanity.com/paper/2410.01987/) (2024)
- [A Dataset and BERT-based Models for Targeted Sentiment Analysis on Turkish Texts](https://mlsanity.com/paper/2205.04185/) (2022)
- [Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models](https://mlsanity.com/paper/2103.06057/) (2021)
- [A Comparative Analysis of Noise Reduction Methods in Sentiment Analysis on Noisy Bangla Texts](https://mlsanity.com/paper/2401.14360/) (2024)
- [MONOVAB : An Annotated Corpus for Bangla Multi-label Emotion Detection](https://mlsanity.com/paper/2309.15670/) (2023)
- [Transfer Learning for Multi-lingual Tasks -- a Survey](https://mlsanity.com/paper/2110.02052/) (2021)
- [Emotions are Subtle: Learning Sentiment Based Text Representations Using Contrastive Learning](https://mlsanity.com/paper/2112.01054/) (2021)
- [A Comprehensive Review of Visual-Textual Sentiment Analysis from Social Media Networks](https://mlsanity.com/paper/2207.02160/) (2022)
- [OneLove beyond the field -- A few-shot pipeline for topic and sentiment analysis during the FIFA World Cup in Qatar](https://mlsanity.com/paper/2408.02520/) (2024)
- [Measuring Linguistic Diversity During COVID-19](https://mlsanity.com/paper/2104.01290/) (2021)
- [Unsupervised Sentiment Analysis by Transferring Multi-source Knowledge](https://mlsanity.com/paper/2105.11902/) (2021)
- [Towards Financial Sentiment Analysis in a South African Landscape](https://mlsanity.com/paper/2106.10004/) (2021)
- [Affect as a proxy for literary mood](https://mlsanity.com/paper/2304.02894/) (2023)
- [Natural language processing on customer note data](https://mlsanity.com/paper/2305.02029/) (2023)
- [A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews](https://mlsanity.com/paper/2306.07786/) (2023)
- [Sentiment Analysis in Digital Spaces: An Overview of Reviews](https://mlsanity.com/paper/2310.19687/) (2023)
- [Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data](https://mlsanity.com/paper/2312.03095/) (2023)
- [TOPol: Capturing and Explaining Multidimensional Semantic Polarity Fields and Vectors](https://mlsanity.com/paper/2510.25069/) (2025)

## Abstract (arXiv)

Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. We present a computer-assisted literature review, where we utilize both text mining and qualitative coding, and analyze 6,996 papers from Scopus. We find that the roots of sentiment analysis are in the studies on public opinion analysis at the beginning of 20th century and in the text subjectivity analysis performed by the computational linguistics community in 1990's. However, the outbreak of computer-based sentiment analysis only occurred with the availability of subjective texts on the Web. Consequently, 99% of the papers have been published after 2004. Sentiment analysis papers are scattered to multiple publication venues, and the combined number of papers in the top-15 venues only represent ca. 30% of the papers in total. We present the top-20 cited papers from Google Scholar and Scopus and a taxonomy of research topics. In recent years, sentiment analysis has shifted from analyzing online product reviews to social media texts from Twitter and Facebook. Many topics beyond product reviews like stock markets, elections, disasters, medicine, software engineering and cyberbullying extend the utilization of sentiment analysis