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Full-Text Articles in Computer Engineering
Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy
Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy
Dissertations
Sentiment Analysis also known as opinion mining is a type of text research that analyses people’s opinions expressed in written language. Sentiment analysis brings together various research areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is fast becoming of major importance to companies and organizations as it is started to incorporate online commerce data for analysis. Often the data on which sentiment analysis is performed will be reviews. The data can range from reviews of a small product to a big multinational corporation. The goal of performing sentiment analysis is to extract information from those …
Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir
Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir
Dissertations
Sentiment analysis is also known as Opinion mining or emotional mining which aims to identify the way in which sentiments are expressed in text and written data. Sentiment analysis combines different study areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is quickly becoming a key concern for businesses and organizations, especially as online commerce data is being used for analysis. Twitter is also becoming a popular microblogging and social networking platform today for information among people as they contribute their opinions, thoughts, and attitudes on social media platforms over the years. Because of the large …
Finetuning Pre-Trained Language Models For Sentiment Classification Of Covid19 Tweets, Arjun Dussa
Finetuning Pre-Trained Language Models For Sentiment Classification Of Covid19 Tweets, Arjun Dussa
Dissertations
It is a common practice in today’s world for the public to use different micro-blogging and social networking platforms, predominantly Twitter, to share opinions, ideas, news, and information about many things in life. Twitter is also becoming a popular channel for information sharing during pandemic outbreaks and disaster events. The world has been suffering from economic crises ever since COVID-19 cases started to increase rapidly since January 2020. The virus has killed more than 800 thousand people ever since the discovery as per the statistics from Worldometer [1] which is the authorized tracking website. So many researchers around the globe …
Enhancing Partially Labelled Data: Self Learning And Word Vectors In Natural Language Processing, Eamon Mcentee
Enhancing Partially Labelled Data: Self Learning And Word Vectors In Natural Language Processing, Eamon Mcentee
Dissertations
There has been an explosion in unstructured text data in recent years with services like Twitter, Facebook and WhatsApp helping drive this growth. Many of these companies are facing pressure to monitor the content on their platforms and as such Natural Language Processing (NLP) techniques are more important than ever. There are many applications of NLP ranging from spam filtering, sentiment analysis of social media, automatic text summarisation and document classification.
Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley [Thesis]
Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley [Thesis]
Dissertations
Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base.
“How Short Is A Piece Of String?”: An Investigation Into The Impact Of Text Length On Short-Text Classification Accuracy, Austin Mccartney
“How Short Is A Piece Of String?”: An Investigation Into The Impact Of Text Length On Short-Text Classification Accuracy, Austin Mccartney
Dissertations
The recent increase in the widespread use of short messages, for example micro-blogs or SMS communications, has created an opportunity to harvest a vast amount of information through machine-based classification. However, traditional classification methods have failed to produce accuracies comparable to those obtained from similar classification of longer texts. Several approaches have been employed to extend traditional methods to overcome this problem, including the enhancement of the original texts through the construction of associations with external data enrichment sources, ranging from thesauri and semantic nets such as Wordnet, to pre-built online taxonomies such as Wikipedia. Other avenues of investigation have …
The Evaluation Of Ensemble Sentiment Classification Approach On Airline Services Using Twitter, Zechen Wang
The Evaluation Of Ensemble Sentiment Classification Approach On Airline Services Using Twitter, Zechen Wang
Dissertations
In the field of sentiment classification, much research has been done on reviews of topics such as movies, software and books. Little research has been done in the airline service domain. In the airline industry, the use of social media as a customer service tool has become a growing phenomenon. The research conducted by Wan and Gao (2015) has proposed an ensemble classification approach for airline service sentiment classification using Twitter data. In accordance, the objective of improving the performance of ensemble classification approach is the primary consideration. This research proposed new hybrid classification approach that uses the state-of-art approach …