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From Brussels with love? Data Analysis of Social Media usage by Czech Members of the European Parliament
Vanka, Boris ; Váška, Jan (advisor) ; Ullrichová, Eliška (referee)
The central theme of this thesis was a deeper understanding of social media communication by Members of the European Parliament (MEPs) elected for Czechia between 2020 and 2022. The author decided to conduct the research due to the influence the politicians maintain (factual within the legislative process and the one based on their authority when co-creating opinions in the public sphere), while a lack of academic studies on such a topic existed, establishing a research gap to be filled. In the past, researchers within the field of political sciences focused primarily on the qualitative dimension of online communication (text analysis) or only one of the social media platforms (mostly Twitter). This approach could uncover sentiments but made it much more challenging to spot trends. Therefore, the data from Facebook, Twitter, and Instagram were obtained via an online provider Zoomsphere, mainly from the parties' leaders in the European elections of 2019. These pieces of information were researched with a data analysis approach, which consisted of nine main steps. After evaluating the research aim, data were identified, collected, extracted, cleaned, aggregated, analyzed, and finally visualized in order to make conclusions based on the outcomes. Once this process was finished, the data were compared...
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Study of Service Activities of the Selected Product within the PLM Module.
Gálíček, Radomír ; Juřica, Pavel (referee) ; Jurová, Marie (advisor)
The service part of the product lifecycle plays a crucial role in ensuring customer satisfaction and generating additional revenue for a company. The aim of this work was to summarize the existing knowledge related to product lifecycles, the knowledge arising from successful implementations in the industry, and to evaluate the service support of specific product lines. The subject of the current situation analysis was to formulate recommendations for extending service contracts based on data analysis to ensure additional revenue for the company.
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Model of Cycling Traffic Intensity in Brno
Eliáš, Radoslav ; Burget, Radek (referee) ; Hynek, Jiří (advisor)
Oddelenie dát v Brne má prístup k viacerým dátovým sadám o počtoch cyklistov. Cieľom práce bolo vytvoriť model integrujúci tieto zdroje pre odbor dopravy magistrátu mesta, aby získali prehľad o tom, ako sa infraštruktúra denne využíva. Každý súbor údajov je agregovaný na inú základnú mapu s mierne odlišnou sieťou ulíc. Táto práca predstavuje algoritmický prístup k porovnávaniu ulíc na základe podobnosti, percentuálneho prekrytia a dalších parametrov. Poskytnuté sú dva algoritmy na porovnávanie geometrie založenej na bodoch a úseckách geometrie. Rovnako aj model priraďujúci lokácie medzi rôznymi dátovými sadami a informačný panel vizualizujúci hodnoty z nich vedľa seba. Robustnosť algoritmov umožnuje ich použitie v akejkoľvek geografickej aplikácii využívajúcej priestorové údaje. Informačný panel poskytuje užitocné informácie o cyklistickej doprave pre bežných používatelov aj odborníkov, ktorí navrhujú infraštruktúru mesta Brna.
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System For Analysis of Biathlon Statistics
Zeman, Ondřej ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
The goal of this bachelor's thesis is to create a web application that downloads biathlon data and statistics and use the technique to get knowledge from data to get interesting and unusual information. In this work are solving descriptive and predictive mining tasks. Clustering algorithms have been used for descriptive mining tasks and for search patterns in course and shooting statistics. Prediction of race results is solved by using multiple linear regression. The application is implemented in Python. Web application is available at https://analysisofbiathlonstatistics.herokuapp.com.
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Analysis of consumer behaviour among DotA 2 players and its effect on individual performance
Krejcar, Vilém ; Krištoufek, Ladislav (advisor) ; Hronec, Martin (referee)
This thesis examine the possible e ect of consumer behaviour, specifically gold sources distribution and e ectiveness in spending, on rank between DotA 2 players. Relevant literature from the past years was summarised and dataset containing more than 91 thousand data points from OpenDota API used to determine the relationship was constructed. Ordered Logistic Regression and K-Means Clustering algorithms were applied on four datasets of 12 variables divided based on the player's position and the outcome of the game, conclud- ing that only a fraction of the variation (McFadden's R2 of 6.2% and Cox & Snell's R2 11.7% on average) has been explained and cluster analysis resulted in a mean accuracy of 38.25%. Those results were supported by the correlation analysis indicating low correlation coe cient values of dependent variable rank. Despite such output, patterns were discovered across individual rank clusters from metrics acclaiming higher e ectiveness of more experienced players re- garding consumer behaviour with strong statistical significance. It has been concluded that the e ect is present, yet its magnitude by itself is not su cient to predict the regressand. The outcome implies possible presence of other vari- ables that have an e ect on the explained variable which are not included in the...
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RQA System Anomaly Detection
Lorenc, Jan ; Jeřábek, Kamil (referee) ; Pluskal, Jan (advisor)
The aim of the theses is to design and implement a machine learning model for anomaly detection in Y Soft's RQA system. Owing to the microservice architecture, an anomaly is considered to be a recurring occurrence of outliers in durations of service requests or a considerable variance in error rate. The thesis outlines the current data collection process in the system and defines what kind of data describe the state of the system. It devises a suitable format of data storage for its subsequent analysis. It presents algorithms commonly used to solve anomaly detection problems. The anomaly detection is designed and implemented using cluster analysis and statistical methods. Finally, the thesis evaluates the quality of the detection and the achieved results.
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ALVAO Service Desk Data Analysis and Reporting
Václavík, Marek ; Novák, Lukáš (referee) ; Kříž, Jiří (advisor)
The diploma thesis focuses on the analysis of the current state of reporting and data analysis of the ALVAO Service Desk system in the company's internal operation. Based on the findings of deficiencies, a new method of reporting and data analysis on the Microsoft Power BI platform is proposed. The proposal includes the entire Power BI feature cycle from data accessing to sharing.
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Exploratory Analysis of Big Data in "jmenomesto"
Trampeška, Václav ; Plchot, Oldřich (referee) ; Landini, Federico Nicolás (advisor)
Tato práce se zabývá analýzou databáze online hry Jméno, město. V této hře mají hráči za úkol adekvátně odpovídat na zadané kategorie odpovědmi začínající na zadané písmeno. Práce analyzuje evoluci chování hráčů během existence hry a chování hráčů v různých zemích a kulturách v rámci stejného i jiného jazyka na základě popularity různých odpovědí. Pro zjednodušení vykonávání těchto analýz byla vyvinuta webová aplikace umožňující snadnou kolekci a vizualizaci dat v grafech bez nutnosti znalosti databázové struktury a dotazovacího jazyka. Výsledky navržených analyzačních metod jsou porovnávány s daty služby Google Trends za účelem zjištění podobností mezi daty sledovanými ve hře a internetovým vyhledáváním. Z toho porovnání vyplývá, že navržené metody mohou dávat smysluplné výsledky a databáze tedy může být vhodnou pro vykonávání dalších konkrétně zaměřených analýz. Práce dále, i na základě výsledků analýz, navrhuje změny pro zlepšení hry v rámci hráčského prožitku a výdělečnosti.
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Smart metering data analytics
Ševčík, Prokop ; Klusáček, Jan (referee) ; Drápela, Jiří (advisor)
The thesis focuses on using data from smart meters based on two-way communication in distribution system. It describes hardware structure of smart meter and measurements of electrical quantities. The thesis summarizes multiple smart metering use cases in DS. It reviews actual implementation of use cases in DS and it evaluates data available from smart meters. Data analytics tools for DS analysis are presented based on possible use cases
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