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Text mining at multiple granularity: leveraging subwords, words, phrases, and sentences
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Word Sense Disambiguation Using Prior Probability Estimation Based on the Korean WordNet
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In: Electronics; Volume 10; Issue 23; Pages: 2938 (2021)
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Sentiment-Target Word Pair Extraction Model Using Statistical Analysis of Sentence Structures
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In: Electronics; Volume 10; Issue 24; Pages: 3187 (2021)
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Political analytics on election candidates and their parties in context of the US Presidential elections 2020
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Abstract:
The availability of internet services in the United States and rest of the world in general in the modern past has contributed to more traction in the social network platforms like Facebook, Twitter, Instagram, YouTube, and much more. This has made it possible for individuals to freely speak and express their sentiments and emotions towards the society. Social media has also made it possible for bringing people closer by making the world a global village. There are influencers who promote products on social media platforms and politicians run their campaigns online for broader reach. Social media has become the fuel for globalization. In 2020, the United State Presidential Elections saw around 1.5 million tweets on Twitter specifically for the Democratic and Republican party, Joe Biden, and Donald Trump, respectively. The tweets involve people’s sentiments and opinions towards the two political leaders (Joe Biden and Donald Trump) and their parties. The computational study of beliefs, sentiments, evaluations, perceptions, views, and feelings conveyed in text is known as sentiment analysis. The political parties have used this technique to run their campaigns and understand the opinions of the public. It has also enabled the modification of their campaigns accordingly. In this thesis, during the voting time for the United States Elections in 2020, we conducted text mining on approximately 1.5 million tweets received between 15th October and 8th November that address the two mainstream political parties in the United States. We aimed at how Twitter users perceived for both political parties and their candidates in the United States (Democratic Party and Republican Party) using VADER (Valence Aware Dictionary and sEntiment Reasoner) a sentiment analysis tool that is tailored to discover the social media emotions, with a lexicon and rule-based sentiment analysis. The results of the research were the Democratic Party’s Joe Biden regardless of the sentiments and opinions in the in Twitter showing Donald Trump could win. ; Master of Science (M.Sc.) in Computational Sciences
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Keyword:
data mining; Donald Trump; electoral college; Joe Biden; lexical analysis; negative polarity; positive polarity; Sentiment analysis; text mining; tweets; Twitter; U.S. elections 2020; voting/elections; word cloud; word tokenization
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URL: https://zone.biblio.laurentian.ca/handle/10219/3733
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| 6 |
Detection of attacks in the corporate network using the rules of fuzzy logic ; Виявлення атак в корпоративній мережі за допомогою правил нечіткої логіки
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In: Science-based technologies; Том 48, № 4 (2020); 470-477 ; Наукоемкие технологии; Том 48, № 4 (2020); 470-477 ; Наукоємні технології; Том 48, № 4 (2020); 470-477 (2020)
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Analysis of the relationship between Saudi twitter posts and the Saudi stock market
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Identifying Mubasher software products through sentiment analysis of Arabic tweets
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Arabic text classification methods: systematic literature review of primary studies
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| 11 |
A Shallow Parsing Approach to Natural Language Queries of a Database
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| 12 |
Использование векторных методов представления слов в задачах выявления трендов ... : Vector word representation methods in trend detection tasks ...
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Discovery of topological constraints on spatial object classes using a refined topological model
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In: Journal of Spatial Information Science (2019)
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Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation
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In: Sensors ; Volume 19 ; Issue 7 (2019)
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| 15 |
Recognition of American Sign Language Gestures in a Virtual Reality Using Leap Motion
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In: Applied Sciences ; Volume 9 ; Issue 3 (2019)
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| 16 |
QUERIES STRUCTURING FOR SOLVING GRAMMAR AND LEXICAL SEMANTIC PROBLEMS BY MEANS OF CORPUS TOOLS
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In: Новітня лінгвістика; № 4 (2019): ; 18-28 ; Advanced Linguistics; № 4 (2019): Advanced Linguistics; 18-28 ; 2663-6646 ; 2617-5339 (2019)
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| 17 |
Analysis of scientific production based on trending research topics. An Artificial Intelligence case study
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| 18 |
Improving Document Representation Using Retrofitting
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In: Electronic Theses and Dissertations (2019)
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Merging of Numerical Intervals in Entropy-Based Discretization
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: MDPI, 2019
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| 20 |
Using Twitter to understand the human bowel disease community: exploratory analysis of key topics
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