Papers with sentiment analyzer
Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums (2022.lrec-1)
Copied to clipboard
Ishani Mondal, Kalika Bali, Mohit Jain, Monojit Choudhury, Jacki O’Neill, Millicent Ochieng, Kagnoya Awori, Keshet Ronen
| Challenge: | a quantitative linguistic analysis of multilingual peer supporters in health-focused WhatsApp forums in Kenya is needed. |
| Approach: | They conduct a quantitative linguistic analysis of the language usage patterns of multilingual peer supporters in two health-focused WhatsApp forums in Kenya. |
| Outcome: | The proposed language analyzer can be used to analyze language usage patterns in two health-focused WhatsApp forums in Kenya. |
Syntactical Analysis of the Weaknesses of Sentiment Analyzers (D18-1)
Copied to clipboard
| Challenge: | polarity items are lexical items that can only appear in specific licensing contexts. |
| Approach: | They analyze sentiment analyzers for negative polarity items and a set of 150 test sentences . they describe a syntactic phenomenon that an ideal sentiment analyzeur must understand . |
| Outcome: | The proposed method focuses on two sentential structures: downward entailment and non-monotone quantifiers. |
Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew (C18-1)
Copied to clipboard
| Challenge: | Existing sentiment analyzers for MRLs that use tokens and morpheme-based representations have no empirically studied effects of representation choices on neural sentiment analysis. |
| Approach: | They develop a sentiment analysis benchmark for Hebrew based on 12K social media comments and provide two instances of data. |
| Outcome: | The proposed benchmarks show that representation choices have measurable effects on task perfromance and that they vary depending on architecture type. |
SentiArabic: A Sentiment Analyzer for Standard Arabic (L18-1)
Copied to clipboard
| Challenge: | Sentiment analysis is a process of applying computational approaches to identify attitudes, emotions and opinions in text, speech and visual data. |
| Approach: | They propose a sentiment analyzer that identifies the overall contextual polarity for Arabic text. |
| Outcome: | The proposed system achieves an F-score of 76.5% when evaluated on a blind test set. |
Powering Comparative Classification with Sentiment Analysis via Domain Adaptive Knowledge Transfer (2021.emnlp-main)
Copied to clipboard
| Challenge: | Comparative Preference Classification (CPC) is a natural language processing task that predicts whether a preference comparison exists between two entities in a given sentence . |
| Approach: | They propose a sentiment analyzer that learns sentiments to individual entities via domain adaptive knowledge transfer. |
| Outcome: | Experiments on the CompSent-19 dataset present a significant improvement on the F1 scores over the best existing CPC approaches. |
Learning to Control the Fine-grained Sentiment for Story Ending Generation (P19-1)
Copied to clipboard
| Challenge: | Existing studies focus on controlling the sentiment of story endings. |
| Approach: | They propose a generic and novel framework which controls fine-grained sentiment intensity for automatic story ending generation without manually annotating sentiment labels. |
| Outcome: | The proposed framework can generate story endings which meet the given sentiment intensity better. |