Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 20 for “"Sentiment classification"”.
-
A New Hybrid Approach to Sentiment Classification
… and subsequent advancement of the field of Sentiment Analysis. Various issues have arisen from these, such as difficulty in locating these opinions in a body of text, as well as determining the sentiment/polarity of these opinions. To tackle the issue of opinion polarity determination, a …
-
Fine-grained sentiment analysis for customer review
… technologies in many applications in real-life. Sentiment analysis, which has devoted to know others' think or feel about an experience or an item and hence take an action, is one of the most developed area in both academia and industry. Among sentiment analysis, fine-grained aspect sentiment …
-
Few-Shot Semi-Supervised Robust Text Classification with MAML
The need for few-shot semi-supervised text classification arises in a variety of applications, including, e.g., recommendation systems classifying textual content such as product descriptions or news articles based on limited amounts of user feedback. In such settings, existing supervised methods …
-
Image captioning using compositional sentiments
… non-factual aspects. This is caused by lack of sentiment information in the caption dataset. We solve this issue by preprocessing the text captions in an image captioning dataset with a sentiment analyzer to determine sentiment scores of all images in the training dataset. The model trained from …
-
Using Sentiment Analysis on online product reviews for determining fairness
… a simile mechanism. Our hypothesis claims that sentiment analysis can help to red flag unfair reviews and, consequently, simplify this difficult process. For that, we measure the correlation between unfairness and sentiments to check how much emotions are manipulated to guide shopping …
-
Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English
… of opinion-rich resources, opinion mining and sentiment analysis has received increasing attention. Sentiment analysis is one of the most effective ways to find the opinion of authors. By mining what people think, sentiment analysis can provide the basis for decision making. Most of the objects …
-
The role of approximate negators in modeling the automatic detection of negation in tweets
… have been made in the performance of sentiment analysis tools, the automatic detection of negated text (which affects negative sentiment prediction) still presents challenges. More research is needed on new forms of negation beyond prototypical negation cues such as “not” or “never.” …
-
Hybrid Words Representation for the classification of low quality text
… natural language ambiguities. The existing sentiment classification methods are mainly for document and clean textual data which can not capture relationship, different attributes and characteristics within tweet messages. Social media analysis, especially the analysis of tweet messages on …
-
Analysing and Mitigating Classification Bias for Text-based Foundation Models
The objective of text classification is to categorise texts into one of several pre-defined classes. Text classification is a standard natural language processing (NLP) task with various applicability in many domains, such as analysing the evolving sentiment of users on a platform, identifying and …
-
Contextual lexicon-based sentiment analysis for social media.
Sentiment analysis concerns the computational study of opinions expressed in text. Social media domains provide a wealth of opinionated data, thus, creating a greater need for sentiment analysis. Typically, sentiment lexicons that capture term-sentiment association knowledge are commonly used to …
-
Representation and learning schemes for sentiment analysis.
… novel techniques of improving the performance of sentiment analysis of text systems. Thes include feature extraction and selection, enrichment of the document representation and exploitation of the ordinal structure of rating classes. The techniques were evaluated on four sentiment-rich corpora, …
-
Structural exploration and inference of the network
… In the first part, a learning-based method for classification of online reviews that achieves better classification accuracy is extended. Automatic sentiment classification is becoming a popular and effective way to help online users or companies to process and make sense of customer reviews. …
-
Automatic identification of representative content on Twitter
… a method to identify the specific ideas and sentiments that represent the overall conversation surrounding a topic or event as reflected in collections of tweets. We have developed this method in the context of the 2016 US presidential elections. We present and evaluate a large scale data …
-
Information extraction from digital social trace data with applications to social media and scholarly communication data
… communication data like tweets tagged with sentiment, tweets about a search query, and Facebook group posts. For social media, new text classification categories are introduced, with the aim of identifying enthusiastic and supportive users, via their tweets. Additionally, the correlation …
-
Evolutionary deep learning
… across a wide range of image and sentiment classification problems. We further develop an algorithm that automatically determines whether a given data science problem is of classification or regression type, successfully choosing the correct problem type with more than 95% …
-
Social analytics for health integration, intelligence, and monitoring
… Instance Map, Distribution Map, Filter Map, and Sentiment Trend to investigate public health threats in space and time. The third objective is to capture, analyze and quantify public health concerns through sentiment classifications on Twitter data. For traditional public health surveillance …
-
Novel Algorithms for Understanding Online Reviews
… models for the document-level multi-aspect sentiment analysis (DMSA) task, which can help us to not only recover missing aspect-level ratings and analyze sentiment of customers, but also detect aspect and opinion terms from reviews. We conduct three studies in this research direction. In the …
-
Knowledge Acquisition from User Reviews for Interactive Question Answering
… phone features. In order to investigate this, a sentiment classification system is also employed to distinguish between features mentioned in positive and negative contexts. The detailed evaluation and error analysis of the methods proposed form an important part of this research and ensure that …
-
Role of semantic indexing for text classification.
… suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are treated independently of one another. However, the expressiveness of natural language means that lexically different terms …