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.
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Showing 1 to 20 of 173 for “"sentiment analysis"”.
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Semantic Sentiment Analysis of Microblogs
… political issues. A wide range of approaches to sentiment analysis on Twitter, and other similar microblogging platforms, have been recently built. Most of these approaches rely mainly on the presence of affect words or syntactic structures that explicitly and unambiguously reflect sentiment …
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Compact features for sentiment analysis
… features to use for machine learning of sentiment analysis and related tasks. This task is frequently approached using a Bag of Words representation -- one feature for each word encountered in the training data -- which can easily number in the thousands or tens of thousands. This thesis …
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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, …
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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 …
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Sentiment analysis and real-time microblog search
… thesis sets out to examine the role played by sentiment in real-time microblog search. The recent prominence of the real-time web is proving both challenging and disruptive for a number of areas of research, notably information retrieval and web data mining. User-generated content on the …
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Applying Deep Learning on Financial Sentiment Analysis
… the literature has been proved that the market sentiment could predict asset prices. Specifically, it has been shown that the stock market movement is related to financial news and social media events. Thus, it becomes necessary to extract the sentiment of the financial news. We explicitly …
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Multi-theme sentiment analysis with sentiment shifting
Business reviews contain rich sentiment on multiple themes, disclosing more interesting information than the overall polarities of documents. When it comes to fine-grained sentiment analysis, given any segment of text, we are not only interested in overall polarity of such segment, but also the …
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Aspect-based sentiment analysis for social recommender systems.
… of both dependency relations and frequent noun analysis is proposed. Thereafter, this thesis presents how extracted aspects can be used to structure opinionated content enabling sentiment knowledge to enrich product representations. Second, a novel method to integrate aspect-level sentiment …
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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 …
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Consumer Acceptance of Beer: An Automated Sentiment Analysis Approach
… FC data is typically analyzed using text analysis done by hand and is very cumbersome to organize and interpret. There is a growing need and interest to add to the library of data analysis tools used to understand FC data and consumer acceptance studies. Sentiment analysis is an opinion …
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A vector space approach for aspect-based sentiment analysis
… for the research problem of Aspect-Based Sentiment Analysis (ABSA), which attempts to capture both semantic and sentiment information encoded in user generated content such as product reviews. In particular, we target three ABSA sub-tasks: aspect term extraction, aspect category detection, …
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A longitudinal sentiment analysis of the #FeesMustFall campaign on Twitter
Submitted in fulfillment of the requirements for the Degree of Masters of Information and Communications Technology, Durban University of Technology, Durban, South Africa, 2019.
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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 …
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Detección de estados de ánimo mediante sentiment analysis en hispanohablantes
… Spotting Technique (KST) for text treatment, and Sentiment Analysis based on only Natural Language Processing (NLP) concepts for text analysis. A mobile application with chatbot interface and a bot that invites the user to give details about their mood through questions validated by an expert, are …
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Fuzzy rough set methods for emotion detection and sentiment analysis
… taalverwerking zoals emotiedetectie en sentimentanalyse. In het bijzonder werken we met ordinale multiclassificatie voor het categoriseren van emotie-intensiteit; binaire classificatie voor het detecteren van aanstootgevende taal, het aanzetten tot haat, ironie en sarcasme; en …
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Text mining with word embedding for outlier and sentiment analysis
… text data. Word embedding is an emerging text analysis technique that leverages the fine-grained statistics of context information to map each word to a vector in the embedding space which reflects the semantic proximity between words. Embedding techniques not only enrich the statistical …
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Real-time video sentiment analysis through the use of snapshots
There are many types of emotions that one can experience and they usually have a direct impact on a person's behaviour. Emotions can be conveyed in several ways such as gestures/body movement, words or facial expressions and this dissertation we aim to distinguish the emotional state of a person …
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Sentiment Analysis with Language Models on Finnish Workplace Well-Being Surveys
… investigation into using language models and sentiment classifications as a solution. We tested three different methodologies for this purpose, traditional machine learning with learned embeddings, generative language methods, and fine-tuned BERT models. To our knowledge, this is the first …
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Graph-based approaches for semi-supervised and cross-domain sentiment analysis
… people's opinions, thoughts, speculations and sentiments and is a valuable source of information for companies, organisations and individual users. This has led to the emergence of the eld of sentiment analysis, which deals with the automatic extraction and classi cation of sentiments expressed …
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