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 794 for “"sentiment"”.
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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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INVESTOR ATTENTION AND SENTIMENT
Investor sentiment and attention are often linked to the same non-economic events making it difficult to understand why and how asset prices are affected. This thesis disentangles these two potential drivers of market behaviour by studying how investors react to sports outcomes, weather conditions …
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Large Scale Aggregated Sentiment Analytics
In the past years we have witnessed Sentiment Analytics becoming increasingly popular topic in Information Retrieval, which has established itself as a promising direction of research. With the rapid growth of the user-generated content represented in blogs, forums, social networks and micro-blogs, …
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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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Investor sentiment and stock returns
… seem to relate to previous proxies for investor sentiment, however, when I examine survey measures of interest rates and consumer confidence we find a relationship. I then examine how sentiment affects the cross section of stock returns, consistent with predictions I find that small stocks earn …
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Information and sentiment in financial markets
… information. The second paper measure news sentiment using BERT and explores return predictability based on a new database, Refinitiv Machine Readable News (MRN). The resulting portfolio achieves an annualized Sharpe ratio of 3.96, significantly higher than that of a passive investment (as …
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Corporate Bond Liquidity and Investor Sentiment
I evaluate the effect of firm-level investor sentiment derived from Twitter feed and news stories on a firm’s bond liquidity. I employ an ordinary least squares regression to examine the relationship between firm-level investor sentiment and corporate bond liquidity. The results indicate that a …
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Outsider trading: trading on twitter sentiment
… establish if a relationship between the investor sentiment generated from social media posts, such as Tweets, and the return on securities exists. If a relationship exists, one would be able to obtain an informational advantage from public information and outperform the market on a risk-adjusted …
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Extending volatility models with market sentiment indicators
… au- toregressive model (HAR) by including market sentiment indicators based on Google search volume and Twitter sentiment. We have analysed 30 com- panies of the Dow Jones index for a period of 15 months. We have performed out-of-sample forecast and compiled a ranking of the extended models based …
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Multi-Modal Topic Sentiment Analytics for Twitter
Sentiment analysis has proven to be very successful in text applications. Social media is also considered a quite rich source to get data regarding user’s behaviors and preference. Identifying social context would make the sentiment analysis more meaningful to the applications. Due to the limited …
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Understanding Narratives through Sentiment, Emotions and Events
… Initially, we test and improve the robustness of sentiment analyser models on different genres, including personal narratives and financial news. Then, we investigate the extraction and representation of the fluctuations of the emotional state conveyed by the unfolding events of personal …
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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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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 …
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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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