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- Creators: Department of Finance
- Creators: Computing and Informatics Program
Description
Predictive analytics have been used in a wide variety of settings, including healthcare, sports, banking, and other disciplines. We use predictive analytics and modeling to determine the impact of certain factors that increase the probability of a successful fourth down conversion in the Power 5 conferences. The logistic regression models predict the likelihood of going for fourth down with a 64% or more probability based on 2015-17 data obtained from ESPN’s college football API. Offense type though important but non-measurable was incorporated as a random effect. We found that distance to go, play type, field position, and week of the season were key leading covariates in predictability. On average, our model performed as much as 14% better than coaches in 2018.
ContributorsVoeller, Michael Jeffrey (Co-author) / Blinkoff, Josh (Co-author) / Wilson, Jeffrey (Thesis director) / Graham, Scottie (Committee member) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Twitter is one of the most powerful communication tools ever created. There are over 1.3 billion registered Twitter users (Smith, 2016). 100 million daily people actively use Twitter every day. 6,000 tweets are tweeted every second. Communication has never been so abundant, public, and chronicled. Not only is there a gigantic population to market to, but also a wealth of information about that population to record and draw insights from. However, many companies' Twitter accounts fail to generate popular posts on a regular basis. The content that they produce is ineffective and uninteresting. In my opinion, these companies are failing to take advantage of a huge opportunity. I decided to dive into the Twitter accounts of some of my favorite companies to see what they were doing wrong and how they could improve. My thesis investigates 18 different company Twitter accounts from four different industries: Athletic Apparel, Technology, Online Entertainment, and Car Manufacturing. I pulled 200 tweets from each company and cleaned and organized the data into an Excel spreadsheet. I investigated how certain variables impacted tweet popularity across the four industries. First, I looked at tweet format to determine whether posts, retweets, or replies were the best format. Then, I analyzed how different elements of a tweet's content could impact the tweet's popularity. Specifically, I looked at the effects of including links, hashtags, and questions into the tweet. Next, I tried to determine the optimal tweet length for each industry. And finally, I compared each industry's tweet sentiment preferences. I then summarized my findings into a series of recommendations for companies to improve their tweet popularity.
ContributorsFrame, Christopher James (Author) / Clark, Joseph (Thesis director) / Jenkins, Anthony (Committee member) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
For our collaborative thesis we explored the US electric utility market and how the Internet of Things technology movement could capture a possible advancement of the current existing grid. Our objective of this project was to successfully understand the market trends in the utility space and identify where a semiconductor manufacturing company, with a focus on IoT technology, could penetrate the market using their products. The methodology used for our research was to conduct industry interviews to formulate common trends in the utility and industrial hardware manufacturer industries. From there, we composed various strategies that The Company should explore. These strategies were backed up using qualitative reasoning and forecasted discounted cash flow and net present value analysis. We confirmed that The Company should use specific silicon microprocessors and microcontrollers that pertained to each of the four devices analytics demand. Along with a silicon strategy, our group believes that there is a strong argument for a data analytics software package by forming strategic partnerships in this space.
ContributorsLlazani, Loris (Co-author) / Ruland, Matthew (Co-author) / Medl, Jordan (Co-author) / Crowe, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Economics (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Hugh Downs School of Human Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
SEO stands for search engine optimization. It is a powerful data analytics tool that can enhance a company’s online platform. The goal of SEO is to utilize Google’s algorithm in order to have your website ranked #1 on the SERP (search engine results page). This will increase user traffic to your site because more users will click on your page. My eyes were first opened to the SEO industry during my internship at Clutch where we used a balance of intercept and intent traffic to capture a large target audience in order to convert them into paying customers. Even though SEO is a newer strategy, it has a higher return on investment than typical paid advertisements. With this, smaller companies can learn SEO and outsmart the bigger companies, while using a smaller marketing budget.
ContributorsHaas, Shelby (Author) / Darcy, David (Thesis director) / Coleman, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2022-05
Description
The influx of readily available sports data has transformed the landscape of recruitment analysis conducted in European soccer leagues. Clubs now have access to a repository of information that helps to monitor the status of current players and filter those they wish to recruit. Supplemented by extensive financial backing, the teams in the English Premier League have shifted from a local, more traditional approach to a focus on the acquisition of players in international markets. This paper analyzes the rapid effects of implementing a data-driven approach to recruitment and argues that the dominance of Liverpool in the EPL from 2017 to 2022 has stemmed from a superior focus in this data-driven recruitment compared to other clubs in the league, specifically Manchester United. Other teams have recently shifted their structures to model the modern, fast flow of data that the two European super clubs manage each season yet consistently fail to match either. Furthermore, this project establishes the feasible prospect of clubs prioritizing their staffing for data over other departments, including players.
ContributorsKhan, Samdeet (Author) / Watrous, Lisa (Thesis director) / Gowtham, S. (Committee member) / Barrett, The Honors College (Contributor) / College of Integrative Sciences and Arts (Contributor) / Computing and Informatics Program (Contributor)
Created2022-05
Description
The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose of this paper is to describe the methodology used in the creation of a new set of curricula for those attempting to learn how to use the Dynamic Traffic Simulation Package with Multi-Resolution Modeling. The current DLSim curriculum currently relates information via high-concept terms and complicated graphics. The information in this paper aims to provide a streamlined set of curricula for new users of DLSim, including lesson plans and improved infographics.
ContributorsMills, Alexander (Author) / Zhou, Xuesong (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05