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Cryptocurrencies are notorious for its volatility. But with its incredible rise in price, Bitcoin keep being on the top among the trending topics on social media. Although doubts continue to rise with price, Bloomberg even make critics on Bitcoin as ‘the biggest bubble in the history’, some investors still hold

Cryptocurrencies are notorious for its volatility. But with its incredible rise in price, Bitcoin keep being on the top among the trending topics on social media. Although doubts continue to rise with price, Bloomberg even make critics on Bitcoin as ‘the biggest bubble in the history’, some investors still hold strong enthusiasm and confidence towards Bitcoin. As contradicting opinions increase, it is worthy to dive into discussions on social media and use a scientific method to evaluate public’s non-negligible role in crypto price fluctuation.

Sentiment analysis, which is a notably method in text mining, can be used to extract the sentiment from people’s opinion. It then provides us with valuable perception on a topic from the public’s attitude, which create more opportunities for deeper analysis and prediction.

The thesis aims to investigate public’s sentiment towards Bitcoin through analyzing 10 million Bitcoin related tweets and assigning sentiment points on tweets, then using sentiment fluctuation as a factor to predict future crypto fluctuation. Price prediction is achieved by using a machine learning model called Recurrent Neural Network which automatically learns the pattern and generate following results with memory. The analysis revels slight connection between sentiment and crypto currency and the Neural Network model showed a strong connection between sentiment score and future price prediction.
ContributorsZhu, Xiaoyu (Author) / Benjamin, Victor (Thesis director) / Qinglai, He (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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This thesis studies the area of sentiment analysis and its general uses, benefits, and limitations. Social networking, blogging, and online forums have turned the Web into a vast repository of comments on many topics. Sentiment analysis is the process of using software to analyze social media to gauge the attitudes

This thesis studies the area of sentiment analysis and its general uses, benefits, and limitations. Social networking, blogging, and online forums have turned the Web into a vast repository of comments on many topics. Sentiment analysis is the process of using software to analyze social media to gauge the attitudes or sentiments of the users/authors concerning a particular subject. Sentiment analysis works by processing (data mining) unstructured textual evidence using natural language processing and machine learning to determine a positive, negative, or neutral measurement. When utilized correctly, sentiment analysis has the potential to glean valuable insights into consumers' minds, which in turn leads to increased revenue and improved customer satisfaction for businesses. This paper looks at four industries in which sentiment analysis is being used or being considered: retail/services, politics, healthcare, and finances. The goal of the thesis will be to explore whether sentiment analysis has been used successfully for economic or social benefit and whether it is a practical solution for analyzing consumer opinion.
ContributorsSoumya, Saswati (Author) / Uday, Kulkarni (Thesis director) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / WPC Graduate Programs (Contributor) / Department of Information Systems (Contributor)
Created2014-05
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Only an Executive Summary of the project is included.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs

Only an Executive Summary of the project is included.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
ContributorsVerma, Ria (Author) / Goegan, Brian (Thesis director) / Moore, James (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem

The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem was a lack of available information offered by mobile application design teams—the initial goal being to work closely with design teams to learn their decision-making methodology. However, every team that was reached out to responded with rejection, presenting a new problem: a lack of access to quality information regarding the decision-making process for mobile applications. This problem was addressed by the development of an ethical hacking script that retrieves reviews in bulk from the Google Play Store using Python. The project was a success—by feeding an application’s unique Play Store ID, the script retrieves a user-specified amount of reviews (up to millions) for that mobile application and the 4 “recommended” applications from the Play Store. Ultimately, this thesis proved that protected reviews on the Play Store can be ethically retrieved and used for data-driven decision making and identifying patterns in an application’s iterative design. This script provides an automated tool for teams to “put a finger on the pulse” of their target applications.
ContributorsDyer, Mitchell Patrick (Author) / Lin, Elva (Thesis director) / Giles, Charles (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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This thesis looks at the digitalization process holistically. It recognizes that for a digitalization initiative to be successful, it takes input from multiple departments and experts from diverse backgrounds. This paper will be evaluating the interconnectivity needed between the supply chain and human resources departments to spearhead the creation of

This thesis looks at the digitalization process holistically. It recognizes that for a digitalization initiative to be successful, it takes input from multiple departments and experts from diverse backgrounds. This paper will be evaluating the interconnectivity needed between the supply chain and human resources departments to spearhead the creation of a digitalization team. Both sectors must have a firm understanding of the other’s needs, in order to acquire, train, and maintain people who will have the necessary hard and soft skills to develop the digital processes. After conducting extensive research around hiring and training, the researchers identified several best practices that companies can utilize to build a successful digital logistics team. Regarding hiring, companies can improve their current practices by collaborating with universities to create synergy between enterprise needs and college curriculum, as well as utilizing talent acquisition data analytics. They must also employ targeted recruiting strategies to attract high-quality talent and create explicit and attractive job postings. In addition to hiring, companies must also continuously improve their training initiatives to ensure their team’s success. In order to do so, firms should conduct training needs analysis, personalize training using technology, offer non-traditional learning modalities, provide holistic supply chain training, and create a learning culture.

ContributorsRogers, Morgan Leigh (Co-author) / Veverka, Madison (Co-author) / Byrne, Jared (Thesis director) / Locke, Sandy (Committee member) / School of International Letters and Cultures (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This thesis looks at the digitalization process holistically. It recognizes that for a digitalization initiative to be successful, it takes input from multiple departments and experts from diverse backgrounds. This paper will be evaluating the interconnectivity needed between the supply chain and human resources departments to spearhead the creation of

This thesis looks at the digitalization process holistically. It recognizes that for a digitalization initiative to be successful, it takes input from multiple departments and experts from diverse backgrounds. This paper will be evaluating the interconnectivity needed between the supply chain and human resources departments to spearhead the creation of a digitalization team. Both sectors must have a firm understanding of the other’s needs, in order to acquire, train, and maintain people who will have the necessary hard and soft skills to develop the digital processes. After conducting extensive research around hiring and training, the researchers identified several best practices that companies can utilize to build a successful digital logistics team. Regarding hiring, companies can improve their current practices by collaborating with universities to create synergy between enterprise needs and college curriculum, as well as utilizing talent acquisition data analytics. They must also employ targeted recruiting strategies to attract high-quality talent and create explicit and attractive job postings. In addition to hiring, companies must also continuously improve their training initiatives to ensure their team’s success. In order to do so, firms should conduct training needs analysis, personalize training using technology, offer non-traditional learning modalities, provide holistic supply chain training, and create a learning culture.

ContributorsVeverka, Madison (Co-author) / Rogers, Morgan (Co-author) / Byrne, Jared (Thesis director) / Locke, Sandy (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Before the COVID-19 pandemic, there was a great need for United States’ restaurants to “go green” due to consumers’ habits of frequently eating out. Unfortunately, COVID-19 has caused this initiative to lose traction. While the amount of customers ordering takeout has increased, there is less emphasis on sustainability.<br/>Plastic is known

Before the COVID-19 pandemic, there was a great need for United States’ restaurants to “go green” due to consumers’ habits of frequently eating out. Unfortunately, COVID-19 has caused this initiative to lose traction. While the amount of customers ordering takeout has increased, there is less emphasis on sustainability.<br/>Plastic is known for its harmful effects on the environment and the extreme length of time it takes to decompose. According to the International Union for Conservation of Nature (IUCN), almost 8 million tons of plastic end up in the oceans at an annual rate, threatening not only the safety of marine species, but also human health. Modern food packaging materials have included a blend of synthetic ingredients, trickling into our daily lives and polluting the air, water, and land. Single-use plastic items slowly degrade into microplastics and can take up to hundreds of years to biodegrade.<br/>Due to COVID-19, restaurants have switched to takeout and delivery options to adapt to the new business environment and guidelines enforced by the Center of Disease Control (CDC) mandated guidelines.<br/>Some of these guidelines include: notices encouraging social distancing and mask-wearing, mandated masks for employees, and easy access to sanitary supplies.<br/>This cultural shift is motivating restaurants to search for a quick, cheap, and easy fix to adapt to the increased demand of take-out and delivery methods. This increases their plastic consumption of items such as plastic bags/paper bags, styrofoam containers, and beverage cups. Plastic is the most popular takeout material because of its price and durability as well as allowing for limited contamination and easy disposability.<br/>Almost all food products come in packaging and this, more often than not, is single use. Food is the largest market out of all the packaging industry, maintaining roughly two thirds of material going to food. The US Environmental Protection Agency reports that almost half of all municipal solid waste is made up of food and food packaging materials. In 2014, over 162 million tons of packaging material waste were generated in the states. This typically contains toxic inks and dyes that leach into groundwater and soil. When degrading, pieces of plastic absorb toxins like PCBs and pesticides, and then each piece will in turn release toxic chemicals like Bisphenol A. Even before being thrown away, it causes negative effects for the environment. The creation of packaging materials uses many resources such as petroleum and chemicals and then releases toxic byproducts. Such byproducts include sludge containing contaminants, greenhouse gases, and heavy metal and particulate matter emissions. Unlike many other industries, plastic manufacturing has actually increased production. Demand has increased and especially in the food industry to keep things sanitary. This increase in production is reflective of the increase in waste. <br/>Although restaurants have implemented their own sustainable initiatives to combat their carbon footprint, the pandemic has unfortunately forced restaurants to digress. For example, Just Salad, a fast-food restaurant chain, incentivized customers with discounted meals to use reusable bowls which saved over 75,000 pounds of plastic per year. However, when the pandemic hit, the company halted the program to pivot towards takeout and delivery. This effect is apparent on an international scale. Singapore was in lock-down for eight weeks and during that time, 1,470 tons of takeout and food delivery plastic waste was thrown out. In addition, the Hong Kong environmental group Greeners Action surveyed 2,000 people in April and the results showed that people are ordering out twice as much as last year, doubling the use of plastic.<br/>However, is this surge of plastic usage necessary in the food industry, or are there methods that can be used to reduce the amount of waste production? The COVID-19 pandemic caused a fracture in the food system’s supply chain, involving food, factory, and farm. This thesis will strive to tackle such topics by analyzing the supply chains of the food industry and identify areas for sustainable opportunities. These recommendations will help to identify areas for green improvement.

ContributorsVargas, Cassandra (Author) / Printezis, Antonios (Thesis director) / Konopka, John (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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There does not appear to be a singular variable that determines where companies choose to place their distribution centers, however there are several underlying factors that may alter companies’ decisions on what countries they develop distribution networks in. There are many reasons companies choose a distribution centers’ location: infrastructure,

There does not appear to be a singular variable that determines where companies choose to place their distribution centers, however there are several underlying factors that may alter companies’ decisions on what countries they develop distribution networks in. There are many reasons companies choose a distribution centers’ location: infrastructure, trade barriers, and costs are often considered as well as the supply and demand markets for the product offerings. Countries can alter aspects to increase the number of businesses that operate within their bounds. When a distribution center is constructed local communities benefit from corporate initiatives and funding as well as jobs and access to cheaper products. Countries often utilize taxes and regulation to positively impact the environment when introducing distribution centers to their economy. The goal is to understand the weights of different factors that shape where distribution centers are located and inform decision makers on the aspects they should alter to get the greatest return on investment. The resulting data will display how large retailers have positioned their current warehouse to indicate likely expansions and the factors that are currently affecting location decisions. <br/><br/>The research project asks the following questions:<br/><br/>When determining the best location for distribution centers, what factors have the largest impact on business decisions? <br/>What role do governments play in developing space for companies to conduct business in (how do they update their infrastructure and customs methods including the impact on trade across industries)? <br/>How can governments and the community limit outsourcing and/or bring businesses (and thus distribution centers) closer to home? <br/><br/>When determining distribution center locations, most companies analyze the political and market structure to decide whether they will enter the market. Once companies have chosen the general region they are hoping to gain, infrastructure and costs are analyzed to find to maintain a competitive advantage in cost while maintaining relatively close locations to stores and consumers. Many companies utilize intermodal transportation on a macroscale, however in last mile logistics it is uncommon for large retailers such as Amazon and Walmart to use anything other than trucks (most commonly their own fleet). Governments have a clear role in gaining or limiting business, however, these factors are typically only considered upon entry or due to changes in major trade barriers therefore policy changes are less likely to encourage growth than investments in infrastructure or alterations in economic conditions such as taxes. Consumers and governments should work together to create an environment that fosters business growth in both new companies entering the market and existing companies expanding by creating unique policies that utilize taxes and business investments to invest in infrastructure.

ContributorsMcMahon, Casey Ann (Author) / Brian, Jennifer (Thesis director) / Keane, Katy (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

As online media, including social media platforms, become the primary and go-to resource for traditional communication, news and the spread of information is more present and accessible to consumers than ever before. This research focuses on analyzing Twitter data on the ongoing Russian-Ukrainian War to understand the significance of social

As online media, including social media platforms, become the primary and go-to resource for traditional communication, news and the spread of information is more present and accessible to consumers than ever before. This research focuses on analyzing Twitter data on the ongoing Russian-Ukrainian War to understand the significance of social media during this period in comparison to previous conflicts. The significance of social media and political conflict will be examined through Twitter user analysis and sentiment analysis. This case study will conduct sentiment analysis on a random sample of tweets from a given dataset, followed by user analysis and classification methods. The data will explore the implications for understanding public opinion on the conflict, the strengths and limitations of Twitter as a data source, and the next steps for future research. Highlighting the implications of the research findings will allow consumers and political stakeholders to make more informed decisions in the future.

ContributorsBlavatsky, Sofia (Author) / Hahn, Richard (Thesis director) / Sirugudi, Kumar (Committee member) / Inozemtseva, Julia (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor)
Created2023-05
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With the discovery of “Big Data” and the positive impacts properly using data can have on any and every business, it is no wonder that there has been an explosion of companies choosing to implement many possible uses of data. Consumers and any people who may not fully understand

With the discovery of “Big Data” and the positive impacts properly using data can have on any and every business, it is no wonder that there has been an explosion of companies choosing to implement many possible uses of data. Consumers and any people who may not fully understand the process of collecting, analyzing, and visualizing data may be more easily swayed towards believing something that might not necessarily be true or represented accurately. Often it may feel like every hot topic issue has groups on both sides of the issues using seemingly objective data to prove why their side is correct. Seeing two contradictory sides with seemingly factual data can leave many people confused and unsure what the correct course of action is. With this in mind, I realized that there was a chance the businesses could be creating similar misrepresentations of data to sway customers that the company’s product or service is absolutely a necessity in their lives. After all, the world of marketing and understanding consumer preference is a wildly changing and constant moving target that companies have to navigate. Using data surrounding their products and services to create a desire in consumers to buy and use their offerings seems like a surefire way to successfully target market segments.
As I researched and conducted initial analysis for this project, I quickly ran into a few roadblocks that lead to me needing to pivot off of certain ideas and adapt my initial plans to fit what was actually being done in the current marketing environment. In reality, most businesses are not up for taking the risk of explicitly giving real metrics of their products and services to customers. Due to this, my thesis evolved into finding other ways that companies would use logical appeals to represent their products and comparatively analyze how these companies choose to represent themselves on a social media platform.
ContributorsQueen, Adrianna Louise (Author) / Prince, Linda (Thesis director) / Olsen, Christopher (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05