Fake News Detection with Quantum Machine Learning
Type of DegreePhD Dissertation
Computer Science and Software Engineering
MetadataShow full item record
Social media has become a popular platform as a source of news or information in mod- ern life as a result of its timeliness and convenience, but it raises several critical issues. The leading issue is the spread of fake news on social media. Fake news has been considered a threat to democracy and the credibility of information. Detecting fake news is a more complex problem when compared to other online malicious behaviors. Several studies have proven that machine learning can be effectively leveraged as a solution for fake news detec- tion. However, with the increasing amount of data, traditional machine learning algorithms will face challenges with ingesting and processing large amounts of data. Quantum machine learning can be a viable solution. Quantum machine learning can be leveraged to address this issue. Research has proven that quantum computing can be utilized to solve computa- tionally intensive problems, and quantum algorithms can achieve an exponential or quadratic speed-up for solving the same problems. To explore the application of quantum machine learning techniques within the field of fake news detection, this research leverages the quantum K-Nearest Neighbors (KNN) model, the Quantum Support Vector Machine (QSVM) model, and the Variational Quantum Classifier (VQC). The experiments and results in this research suggest that it is possible to utilize quantum machine learning to effectively address the problem of fake news detection.
Ugunduzi wa Habari bandia na Kujifunza Mashine ya Quantum Aina ya digrii PhD Dissertation Sayansi ya Kompyuta na Uhandisi wa Programu Metadata Show Full Item Rekodi Mitandao ya kijamii imekuwa jukwaa maarufu kama chanzo cha habari au habari katika maisha ya kisasa kama matokeo ya wakati wake na urahisi, lakini inainua masuala kadhaa muhimu. Suala kuu ni kuenea kwa habari bandia kwenye mitandao ya kijamii. Habari bandia zimechukuliwa kuwa tishio kwa demokrasia na uaminifu wa habari. Kugundua habari bandia ni tatizo tata zaidi ikilinganishwa na tabia nyingine mbaya mtandaoni. Uchunguzi kadhaa umethibitisha kwamba kujifunza mashine inaweza kwa ufanisi leveraged kama ufumbuzi kwa ajili ya kugundua habari bandia. Hata hivyo, na kuongezeka kwa kiasi cha data, algorithms jadi mashine kujifunza kukabiliana na changamoto na kumeza na usindikaji wa kiasi kikubwa cha data. Kujifunza kwa mashine ya quantum kunaweza kuwa suluhisho linalofaa. Kujifunza mashine ya quantum inaweza kutumika kushughulikia suala hili. Utafiti umeonyesha kwamba kompyuta ya quantum inaweza kutumika kutatua matatizo computationally-intensive, na algorithms quantum inaweza kufikia exponential au quadratic kasi-up kwa kutatua matatizo sawa. Kwa mfano, katika utafiti wa kugundua habari bandia, watafiti walitumia mfano wa K-Nearest Neighbors (KNN), Quantum Support Vector Machine (QSVM) na Variational Quantum Classifier (VQC). Majaribio na matokeo katika utafiti huu yanaonyesha kuwa inawezekana kutumia kujifunza mashine ya quantum kushughulikia kwa ufanisi tatizo la kugundua habari bandia.