Language Independent Sentiment Analysis
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Abstract (arXiv)
Social media platforms and online forums generate rapid and increasing amount of textual data. Businesses, government agencies, and media organizations seek to perform sentiment analysis on this rich text data. The results of these analytics are used for adapting marketing strategies, customizing products, security and various other decision makings. Sentiment analysis has been extensively studied and various methods have been developed for it with great success. These methods, however apply to texts written in a specific language. This limits applicability to a limited demographic and a specific geographic region. In this paper we propose a general approach for sentiment analysis on data containing texts from multiple languages. This enables all the applications to utilize the results of sentiment analysis in a language oblivious or language-independent fashion.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Dec 2019.
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Citing papers per year: 2021: 7; 2022: 3.
10 papers.
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequencescited by 30
- 2021A k-mer Based Approach for SARS-CoV-2 Variant Identificationcited by 23
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequencescited by 22
- 2022Efficient Approximate Kernel Based Spike Sequence Classificationcited by 18
- 2021Effective and scalable clustering of SARS-CoV-2 sequencescited by 15
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variantscited by 14
- 2021Efficient Analysis of COVID-19 Clinical Data using Machine Learning Modelscited by 6
- 2021Computing Graph Descriptors on Edge Streamscited by 4
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Locationcited by 2
- 2022Information We Can Extract About a User From 'One Minute Mobile Application Usage'cited by 1
- 2022Efficient Approximate Kernel Based Spike Sequence Classification11 Sep 2022
- 2022Information We Can Extract About a User From 'One Minute Mobile Application Usage'27 Jul 2022
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences6 Jan 2022
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants18 Oct 2021
- 2021Efficient Analysis of COVID-19 Clinical Data using Machine Learning Models18 Oct 2021
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Location2 Oct 2021
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequences12 Sep 2021
- 2021Computing Graph Descriptors on Edge Streams2 Sep 2021
- 2021Effective and scalable clustering of SARS-CoV-2 sequences18 Aug 2021
- 2021A k-mer Based Approach for SARS-CoV-2 Variant Identification7 Aug 2021