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 58 for “"Twitter data"”.
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Analyzing Twitter Data for Emergency Management
… information in different emergency event datasets. Results show that significant features vary across different events which indicates that training should happen during the event.
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Framing Crime: An Analysis of News Media Twitter Data
… news briefs through social media platforms like Twitter. Using this method of information sharing, news organizations can instantly reach consumers as events unfold in real time. With character limitations with Twitter, one may assume news organizations use words carefully and succinctly to …
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Estimate Flood Damage Using Satellite Images and Twitter Data
… estimation system did not apply social media data. The theme of this thesis was to evaluate the feasibility of using machine learning models to predict hurricane damage and the input data are social media and satellite imagery. This work involves developing Data Mining approach and a couple of …
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An Approach For Scalable First-Order Rule Learning On Twitter Data
… with graph-based modeling of social media data, to scale up first-order rule learning through Markov Logic Networks on a commodity cluster on large scale Twitter data. SRLearn takes advantage of distributed systems to partition large-scale data into smaller but meaningful partitions based …
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Measuring the Connective Action of Black Lives Matter Activists: A Psychometric Investigation into Twitter Data
… through quantification, illustrate how in-situ data sources can be used for statistical modeling, and provide a resource for activists interested in their use of social media to enact social change.</p> <p>Insights from the content analysis portion include two theoretically contributive terms: …
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A Comparative Study on Feature Extraction and Classification/Clustering of Fake News and Conspiracy Theories from Twitter Data
… detect fake news and conspiracy theories from twitter datasets. The results indicate that the tf-idf method of feature extraction, when implemented with the svm classification algorithm, yields the highest accuracy of 99.6% in comparison to the other algorithms i.e. multinomial naive bayes, …
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Adapting the Standard SIR Disease Model in Order to Track and Predict the Spreading of the EBOLA Virus Using Twitter Data
… developed to track infectious diseases by using data mining of active Twitter accounts and its efficacy was demonstrated during the West African Ebola outbreak of 2014. Using a meme based n-gram semantic usage model to search the Twitter database for indications of illness, flight and death from …
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Data mining Twitter for cancer, diabetes, and asthma insights
<p>Twitter may be a data resource to support healthcare research. Literature is still limited related to the potential of Twitter data as it relates to healthcare. The purpose of this study was to contrast the processes by which a large collection of unstructured disease-related tweets could be …
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A Framework for Hadoop Based Digital Libraries of Tweets
… Scala, HBase, etc.), simply converting the Twitter data into a workable format can be a cumbersome task in itself. This prompted the effort to build a framework that will help in developing code to analyze the Twitter data, run on arbitrary tweet collections, and enable developers to …
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Predicting the Outcomes of Important Events based on Social Media and Social Network Analysis
Twitter is a famous social network website that lets users post their opinions about current affairs, share their social events, and interact with others. It has now become one of the largest sources of news, with over 200 million active users monthly. It is possible to predict the outcomes of …
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Statistical and machine learning models for critical infrastructure resilience
This thesis presents a data-driven approach to improving predictions of critical infrastructure behaviors. In our first approach, we explore novel data sources and time series modeling techniques to model disaster impacts on power systems through the case study of Hurricane Sandy as it impacted the …
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ONet: Search, explore, and visualize hierarchical topic summarization on Twitter using network-OLAP
Multi-dimensional data is one of the most abundant and publicly available data sources for people to access today. It forms hierarchy naturally(e.g., people publish posts about different topics or share information from various countries. Given a topic such as technology, it many form sub-topics …
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An Empirical Approach to Social Networks
… analysis of social network dynamics using Twitter data. We ask whether social networks influence voting decisions, and determine whether or not people make consistent choices based on their tweets or what they believe. We collect Twitter data on a daily basis, with dynamic social network …
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A Computational Study in the Detection of English–Spanish Code-Switches
… English and Spanish in two corpora.</p> <p>Twitter and other social media sites have provided an abundance of linguistic data that is available to researchers to perform countless experiments. Collecting the data is fairly easy if a study is on monolingual text, but if a study requires …
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Large Web Archive Collection Infrastructure and Services
… to standardize the preservation of web archive data. In addition to its preservation purpose, web archive data is also used as a source for research and for lost information recovery. However, the reuse of web archive data is inherently challenging because of the scale of data size and …
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USING SOCIAL MEDIA AS A DATA SOURCE IN PUBLIC HEALTH RESEARCH
… have increasingly looked to social media data as a means of measuring population health and well-being in a less intrusive and more scalable manner compared to traditional public health data sources. In this dissertation, I outline three studies that leverage social media as a data source, …
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A temporal topic model for social trend prediction
… their thoughts and concerns in a large volume of data. While user-generated data from each individual may not provide considerable information, when combined, they include variables which can convey significant events. In this thesis, we pursue the question of whether social media context can …
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Nonlinear network vector autoregression
… is applied. Simulation results and modeling for Twitter data were applied to support our methodology for TNAR models.;For the TNQAR model, we also provide the parameter conditions for the stationary of the time series. Under these parameter conditions, the TNQAR process can be approximated by the …
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Application of Data Analytics for Prediction of Suicide Rates at the State and National Levels
… in two phases; the first using response variable data and explanatory variable data from the same time period, and the second with the response variable data shifted one time period to create a more accurate model for prediction. The models had k-fold R-squared values of 0.676 and 0.675. The …
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Why, New York City? Gauging the Quality of Life Through the Thoughts of Tweeters
<p>As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and …
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