Text mining and its challenges, explore different techniques and tools, and see a case study using Python for sentiment analysis and text classification.

2 views • 25 slides

Examining 2021 local government election turnout trends in Gauteng & impact on major political parties. Longitudinal & spatial analysis of voting patterns. Unpacking reasons for voter behavior shifts. Media narratives vs. political nuances.

1 views • 18 slides

Large Language Models (LLMs) are sophisticated deep learning algorithms capable of understanding and generating human language. These models, trained on massive datasets, excel at various natural language processing tasks such as sentiment analysis, text classification, natural language inference, s

2 views • 83 slides

In 2024, expert currency traders are employing advanced strategies like algorithmic trading, sentiment analysis, cross-currency arbitrage, carry trades, and macroeconomic forecasting. By leveraging technology and market insights, these strategies aim to capitalize on opportunities and mitigate risks

1 views • 7 slides

Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.\n\nknow more>>\/\/ \/web-scraping-food-reviews-data-analysis.php \n

0 views • 12 slides

Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.\n\nknow more>>\/\/ \/web-scraping-food-reviews-data-analysis.php \n

0 views • 12 slides

The market situation in Korea provides valuable insights into outbound travel sentiment during the Chuseok Holidays. With a focus on Hawaii/Maui, the analysis covers economic factors, air seat availability, and competitive landscape, shedding light on consumer behavior and travel preferences.

0 views • 24 slides

Movie reviews data scraping provides a vast dataset for sentiment analysis, offering insights into audience opinions and reactions effectively.\n\nknow more>>\/\/ \/movie-reviews-data-scraping-help-in-analysis.php\n\n

1 views • 7 slides

\nWeb Scraping and Sentiment Analysis of Customer Reviews assesses sentiment. Combined, they provide insights into customer opinions for businesses.\n\nKNOW MORE>>\/\/ \/web-scraping-and-sentiment-analysis-of-customer-reviews.php\n\n

1 views • 9 slides

Deep Transfer Learning and Multi-task Learning involve transferring knowledge from a source domain to a target domain, benefiting tasks such as image classification, sentiment analysis, and time series prediction. Taxonomies of Transfer Learning categorize approaches like model fine-tuning, multi-ta

1 views • 26 slides

Defense Personnel Analytics Center (DPAC) is enhancing their NLP capabilities by implementing a transformer-based platform on the Department of Defense's cloud system ADVANA. The platform focuses on topic modeling and sentiment analysis of open-ended survey responses from various DoD populations. Le

0 views • 13 slides

Delve into the analysis of discrete text prompts and their interpretation of continuous prompts in AI research. The work explores sentiment analysis using pre-trained language models along with recent breakthroughs in spatial reasoning. Discover the challenges in interpreting and optimizing text pro

0 views • 21 slides

Learn how to build a sentiment classifier for movie reviews and identify climate change-related sentences by leveraging active learning. The process involves downloading data, crowdsourcing labeling, and training classifiers to improve accuracy efficiently.

0 views • 47 slides

The thematic analysis of John Keats' "Ode to Autumn" explores the poem's reflection on the beauty of seasonal transitions, emphasizing the melancholic yet serene nature of autumn. Presented by Dr. Mohd Saleem Wani, the analysis delves into Keats' ability to find beauty in the changing landscape and

0 views • 10 slides

Sentiment classification can be done through supervised or unsupervised methods. Unsupervised methods utilize lexical resources and heuristics, while supervised methods rely on labeled examples for training. VADER is a popular tool for sentiment analysis using curated lexicons and rules. The classif

7 views • 17 slides

Explore the methods and techniques for analyzing content effectively. Learn about text analysis, sentiment analysis, and more in this concise guide.

0 views • 60 slides

Sentiment analysis, also known as opinion mining, is the process of analyzing text to determine if it expresses a positive, negative, or neutral sentiment. It has applications in analyzing movie reviews, product feedback, public opinion, and political sentiments. By extracting and analyzing sentimen

0 views • 34 slides

This study introduces WEB-SOBA, a method for semi-automatically building ontologies using word embeddings for aspect-based sentiment analysis. With the growing importance of online reviews, the focus is on sentiment mining to extract insights from consumer feedback. The motivation behind the researc

2 views • 35 slides

Sentiment Analysis using code-mixed data from social media platforms like YouTube is crucial for understanding user emotions. However, the lack of annotated code-mixed data for low-resource languages such as Tulu poses challenges. To address this gap, a trilingual code-mixed Tulu corpus with 7,171 Y

0 views • 10 slides

Growing importance of online reviews highlights the need for automation in sentiment mining. Aspect-Based Sentiment Analysis (ABSA) focuses on detecting sentiments expressed in product reviews, with a specific emphasis on sentence-level analysis. The proposed approach, Deep Contextual Word Embedding

0 views • 34 slides

A survey conducted in May 2017 among 2,006 registered voters in the United States reveals insights into voter sentiment regarding the country’s track and the economy. Findings show voters' perceptions on the track of the nation, the strength of the U.S. economy, and approval ratings for President

0 views • 50 slides

A study conducted by Zheng Li, Ying Wei, Yu Zhang, and Qiang Yang from the Hong Kong University of Science and Technology on utilizing a Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification. The research focuses on sentiment classification testing data of books, training

0 views • 28 slides

The evolution of sentiment analysis on tweets from SemEval competitions in 2013 to 2017 is discussed, showcasing advancements in technology and the shift from SVM and sentiment lexicons to CNN with word embeddings. Aspect-Based Sentiment Analysis, as explored in SemEval2014, involves determining asp

0 views • 23 slides

Motivated by the increasing number of online product reviews, this research explores automation in sentiment mining through Aspect-Based Sentiment Analysis (ABSA). The focus is on sentiment detection for aspects at the review level, using a hybrid approach that combines ontology-based reasoning and

0 views • 26 slides

Sentiment analysis, also known as opinion mining, is the process of evaluating written or spoken language to determine the positivity, negativity, or neutrality of the expression. It involves the systematic identification, extraction, and study of affective states and subjective information using na

0 views • 29 slides

This paper explores the interconnectedness between media content and investor sentiment in the stock market, focusing on the impact of media reports on daily market activity. It delves into the relationship between media pessimism and stock market returns, highlighting how different levels of sentim

0 views • 17 slides

Building on the need for automation due to the increasing volume and significance of online reviews, SASOBUS focuses on Aspect-Based Sentiment Analysis (ABSA). The motivation behind SASOBUS lies in the growth of sentiment mining for product reviews, particularly at the sentence level. Its approach i

0 views • 36 slides

Voter sentiment regarding the direction of the country, the economy, and personal financial situations in September 2017 was analyzed through a survey conducted online among 2,177 registered voters. Results show that voters are more optimistic about the economy than the overall country with a majori

0 views • 48 slides

This project involved gathering a substantial amount of Twitter data for sentiment analysis, including 1717 negative and 687 positive tweets. The data labeling process was initially manual but later automated using a semi-supervised learning technique. A Naive Bayes Classifier was trained using a Ba

0 views • 17 slides

A poll conducted by CIPR Communications in June 2022 gathered sentiment from 1,122 residents across Northern BC communities regarding tourism. The results indicated residents' awareness of tourism's economic impact, concerns about attracting the right visitors, and a moderate correlation between tou

0 views • 18 slides

This study focuses on detecting implicit citations for sentiment detection through various tasks such as finding zones of influence, citation classification, and corpus construction. The research delves into features for classification, highlighting the use of n-grams, dependency triplets, and other

0 views • 14 slides

A cognitive study on extracting subjectivity in sentiment annotation, exploring if humans perform subjective extraction similarly to machines for sentiment analysis. The study investigates sentiment oscillations and different methods adopted based on the nature of subjective documents.

0 views • 14 slides

In this study, Joanna Fane Lineback, Elizabeth Nichols, and Brian F. Sadacca discuss the machine learning approach used to analyze 2020 Census audio recordings. The project aims to develop models that enhance the call experience for callers and customer service representatives (CSRs). Operational go

0 views • 21 slides

Sentiment analysis (SA) or opinion mining is a computational study of opinion, sentiment, appraisal, evaluation, and emotion, which plays a crucial role in influencing behaviors and decision-making processes. This field has gained significance with the rise of social media, offering insights into pu

0 views • 62 slides

This literature review by Paul C. Tetlock explores the role of media in shaping investor sentiment and impacting stock market dynamics. The study delves into the correlation between media pessimism, market prices, trading volume, and volatility, providing insights into how media content affects mark

0 views • 40 slides

Presenter Mariam Biltawi from Princess Sumaya University for Technology in Jordan discusses a research project on enhancing automatic polarity classification of Arabic text using a lexicon-based approach with fuzzy logic. The project utilizes a large-scale Arabic book reviews dataset and a sentiment

1 views • 30 slides

Aspect-Based Sentiment Analysis plays a crucial role in extracting, identifying, and characterizing sentiment content within text data. This analysis helps in understanding how people perceive various aspects in reviews, blogs, and online discussions. The process involves detecting entities, aspects

0 views • 18 slides

This study presents an innovative approach to sentiment analysis at the review level, focusing on aspect-based sentiment analysis (ABSA) using ontologies. Motivated by the increasing volume of product reviews online, the research addresses the challenge of detecting sentiment associated with aspects

0 views • 30 slides

Researchers at the National University of Singapore discuss the concept that a social network is not simply a graph, highlighting key differences such as dynamics, multi-dimensionality, and the challenges in link prediction. The analysis delves into the complexities of social network data compared t

0 views • 24 slides

This presentation discusses the EUROSENTIMENT project focusing on generating multilingual variants for sentiment lexicons. Addressing challenges in sentiment analysis, the project aims to build a shared language resource pool to improve adaptability and interoperability of language resources. Object

0 views • 36 slides