# Advanced Text Analysis Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/advanced-text-analysis-techniques/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the automatic extraction of keywords from textual data using various techniques such as graph-based methods, unsupervised approaches, and neural networks. The research explores the application of linguistic knowledge and statistical information to improve the accuracy of keyword extraction from documents. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t13083 |
| Works | 123 |

## Topic papers all

Showing 15 of 123.

- [CTRL: A Conditional Transformer Language Model for Controllable Generation](https://scholariq.org/papers/ctrl-a-conditional-transformer-language-model-for-controllable-generation/)
- [Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions](https://scholariq.org/papers/multimodal-sentiment-analysis-a-systematic-review-of-history-datasets-multimodal/)
- [Eye-tracking analysis of user behavior in WWW search](https://scholariq.org/papers/eye-tracking-analysis-of-user-behavior-in-www-search/)
- [The effects of statistical training on thinking about everyday problems](https://scholariq.org/papers/the-effects-of-statistical-training-on-thinking-about-everyday-problems/)
- [Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis](https://scholariq.org/papers/convolutional-mkl-based-multimodal-emotion-recognition-and-sentiment-analysis/)
- [A survey of sentiment analysis in social media](https://scholariq.org/papers/a-survey-of-sentiment-analysis-in-social-media/)
- [Sentiment Analysis and Opinion Mining](https://scholariq.org/papers/sentiment-analysis-and-opinion-mining/)
- [HDLTex: Hierarchical Deep Learning for Text Classification](https://scholariq.org/papers/hdltex-hierarchical-deep-learning-for-text-classification/)
- [Combining lexicon-based and learning-based methods for twitter sentiment analysis](https://scholariq.org/papers/combining-lexicon-based-and-learning-based-methods-for-twitter-sentiment/)
- [Knowledge Based Solution Strategies in Medical Reasoning](https://scholariq.org/papers/knowledge-based-solution-strategies-in-medical-reasoning/)
- [The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms](https://scholariq.org/papers/the-validity-of-sentiment-analysis-comparing-manual-annotation-crowd-coding/)
- [Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detection](https://scholariq.org/papers/call-attention-to-rumors-deep-attention-based-recurrent-neural-networks-for/)
- [Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews](https://scholariq.org/papers/senti-lexicon-and-improved-naive-bayes-algorithms-for-sentiment-analysis-of/)
- [Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier](https://scholariq.org/papers/aspect-term-extraction-for-sentiment-analysis-in-large-movie-reviews-using-gini/)
- [A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP](https://scholariq.org/papers/a-tutorial-on-conducting-and-interpreting-a-bayesian-anova-in-jasp-2/)

## Topic primary papers

Showing 15 of 22.

- [A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP](https://scholariq.org/papers/a-tutorial-on-conducting-and-interpreting-a-bayesian-anova-in-jasp-2/)
- [A survey of the applications of text mining in financial domain](https://scholariq.org/papers/a-survey-of-the-applications-of-text-mining-in-financial-domain/)
- [The Random Forests statistical technique: An examination of its value for the study of reading](https://scholariq.org/papers/the-random-forests-statistical-technique-an-examination-of-its-value-for-the/)
- [Mapping Human–Computer Interaction Research Themes and Trends from Its Existence to Today: A Topic Modeling-Based Review of past 60 Years](https://scholariq.org/papers/mapping-human-computer-interaction-research-themes-and-trends-from-its-existence/)
- [Analysing discussions in social networks using group decision making methods and sentiment analysis](https://scholariq.org/papers/analysing-discussions-in-social-networks-using-group-decision-making-methods-and/)
- [Deep LDA : A new way to topic model](https://scholariq.org/papers/deep-lda-a-new-way-to-topic-model/)
- [Extractive Text Summarization Models for Urdu Language](https://scholariq.org/papers/extractive-text-summarization-models-for-urdu-language/)
- [Co-Registration of Eye Movements and Fixation—Related Potentials in Natural Reading: Practical Issues of Experimental Design and Data Analysis](https://scholariq.org/papers/co-registration-of-eye-movements-and-fixation-related-potentials-in-natural/)
- [High Relevance Keyword Extraction facility for Bayesian text classification on different domains of varying characteristic](https://scholariq.org/papers/high-relevance-keyword-extraction-facility-for-bayesian-text-classification-on/)
- [Keyphrase extraction methodology from short abstracts of medical documents](https://scholariq.org/papers/keyphrase-extraction-methodology-from-short-abstracts-of-medical-documents/)
- [The Classification of Short Scientific Texts Using Pretrained BERT Model](https://scholariq.org/papers/the-classification-of-short-scientific-texts-using-pretrained-bert-model/)
- [Evaluation of the citation matching algorithms of CWTS and iFQ in comparison to Web of Science](https://scholariq.org/papers/evaluation-of-the-citation-matching-algorithms-of-cwts-and-ifq-in-comparison-to/)
- [Extracting Fruit Disease Knowledge from Research Papers Based on Large Language Models and Prompt Engineering](https://scholariq.org/papers/extracting-fruit-disease-knowledge-from-research-papers-based-on-large-language/)
- [Integration of Prophet Model and Convolution Neural Network on Wikipedia Trend Data](https://scholariq.org/papers/integration-of-prophet-model-and-convolution-neural-network-on-wikipedia-trend/)
- [Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media](https://scholariq.org/papers/deep-learning-model-for-interpretability-and-explainability-of-aspect-level/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.