Trait Analysis to Facilitate Children’s Books Recommender Systems: Extracting perspective and sentiment traits from book fulltext and descriptions

Recommender systems are a useful tool for match- ing readers with books. However, the lack of user data from children, both due to privacy concerns as well as a low incentive to leave reviews, results in existing systems proving inadequate at recom- mending to the youth. It has been shown that chil- dren have a different relation regarding...

Augmenting Ridership Data with Social Media Data to Analyse the Long-term Effect of COVID-19 on Public Transport

COVID-19 significantly influenced travel behaviours and public attitudes towards public transport. Various studies have illustrated complicated factors related to long-term travel behaviour, indicating difficulty in understanding and predicting post-pandemic long-term travel behaviour via traditional methods. In these complex circumstances,...

Helping users discover perspectives: Enhancing opinion mining with joint topic models

Support or opposition concerning a debated claim such as abortion should be legal can have different underlying reasons, which we call perspectives. This paper explores how opinion mining can be enhanced with joint topic modeling, to identify distinct perspectives within the topic, providing an informative overview from unstructured text. We...

Perspective Discovery in Controversial Debates: An exploration of unsupervised topic models

Since the introduction of the Web, online platforms have become a place to share opinions across various domains (e.g., social media platforms, discussion fora or webshops). Consequently, many researchers have seen a need to classify, summarise or categorise these large sets of unstructured user-generated content. A field related to this task is...

CITYSENT: Sentiment analysis of the Netherlands and Flanders

The department of Urbanism at the TU Delft, our clients, research the sentiment in different places, times, ages or genders and compare them to each other. This report describes the purpose, design, implementation and accuracy of a web tool created to get insights into the sentiment people have, de- ducted from social media. The aim of our...

Recognizing and Handling Negations in Machine Learning

In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise other classification compared to when these (negating) objects are not present. To be more specific, a variant of the XOR problem is present in a small amount of objects in...

Statistical analysis to depict the influence of news headlines on stock volatility

A statistical approach to depict stock volatility based on general news headlines by exploiting Machine Learning methods such as sentiment analysis and neural networks. The results from the analysis are then used in the financial market with a particular trading strategy, called a bottom straddle. We conclude that not enough information can be...

Distance Based Source Domain Selection for Automated Sentiment Classification

Automated Sentiment Classification (SC) on short text fragments has been an upcoming field of research. Different machine learning techniques and word representation models have proven to be successful in classifying sentiment of opinion expressions in various domains, i.e. different topics or source media. However, when training on a source...

Tweet-Based Election Prediction

Twitter is a microblogging service that has more than 500 million messages on a daily basis. Scholars has been utilizing Twitter to monitor people reactions in political activities, such as debates and campaigns. By doing so, some of them claim that a forecast or prediction to an election can be made. Using the data from 2014 Indonesia...

“What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations

We conclude this report with a system design and proof-of-concept to show how an adaptable hybrid sentiment classification system is able to improve sentiment analysis for organisations. GreenOnline, a service company in the field of customer services, wants to be able to quantify sentiment for organisations precisely, to create new services for...

Advancing the Relevance Criteria for Video Search and Visual Summarization

To facilitate finding of relevant information in ever-growing multimedia collections, a number of multimedia information retrieval solutions have been proposed over the past years. The essential element of any such solution is the relevance criterion deployed to select or rank the items from a multimedia collection to be presented to the user....

Context-Sensitive Sentiment Classification of Short Colloquial Text

The wide-spread popularity of online social networks and the resulting availability of data to researchers has enabled the investigation of new research questions, such as the analysis of information diffusion and how individuals are influencing opinion formation in groups. Many of these new questions however require an automatic assessment of...