Capstone Project: Measuring startup strategy and its evolution
Authors : Derek Chen, Alberto Munguia Cisneros, Wangzhi Li, Yinhe Lu, Bernardo Lopez Vicencio
Date: September 2020 - December 2020
Please install the required package using pip install -r requirements.txt
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Directory Notebooks contains all jupyter notebooks we used to produce our report.
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├── ...
├── Notebooks
│ ├── Exploratory Analysis # EDAV of public and private companies data
│ ├── Webscraping # See 'Final_version Multithread' folder for our final version web scraping code
│ ├── NLP # Notebooks for three different approaches(BERT, TF-IDF, Word2vec)
│ └── Prediction # Notebooks for predictions
└── ...
Directory Data contains Public and Startup Data from web scraping.(TO DO)
Please see Progress_Report for our progress reporting along the way.
The purpose of this project is to develop a new analysis of the strategy of firms using text-based machine learning.
The key insight is that distance in the initial statements made by startup companies can be partially indicative of their strategic positioning to each other, and this, in turn, could be an explicative factor of the future performance of the startup.
The expected outcome of the project will be reproducible code and the improvement of the early version of the paper “Measuring Founding Strategy.” by Prof. Jorge Guzman and Aishen Li, which is the base of this project.
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Guzman, J., & Li, A. (2019). Measuring Founding Strategy. Available at SSRN 3489585.
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