The Program Problem

Python has consumed the majority of my time this summer. Each line of code has taken hours to create; the annals of Python Central have been my respite from confusion. Although costing my sanity, the product of these hours is a comprehensive understanding of Python data-mining. Moving forward I am now far more confident in my ability to program/analyze data on a larger scale.

Unfortunately, I have still been unable to create a clean set of data exclusively from Python. This is partially due to my amateur nature and also because I accidentally downloaded a couple nasty viruses that have been wrecking havoc on my computer system.While trying to understand Tweepy and setup my computer for Python properly at the very beginning of the summer I trusted shared code/free supporting programs too deeply and have been suffering the consequences since. As I have been determined to come out of the summer with significant descriptive statistics regardless of programming roadblocks, I have been forced to meticulously compile as much data as possible myself. Therefore, I have spent many, many hours manually sifting through Twitter data – comparing Twitter feeds and content.

Although I believe my greatest learning opportunity has been self-teaching Python, the days I have spent exclusively on Twitter, taking notes and creating a concise data set by hand, have shown me incredible overarching patterns. I have not run statistics on the numbers yet, saving that for next week, but there are evident and significant differences in party uses of Twitter. I have been focusing on the gubernatorial elections taking place this fall. Reflecting on time-honored differences between Republican and Democrat voting patterns, Twitter is used more by Democratic candidates. There are also significant differences in the use of mudslinging tactics (Democrats doing more).

Moving forward, I am still refining my dataset and compiling all the data I can (manually at this point). Next week I will be statistically analyzing my dataset, reflecting on results and beginning a codebook for a future experiment. As always, it is my utmost pleasure to be passionately pursuing improvement and academic knowledge at the behest of the Charles Center.

Comments

  1. lailadrury says:

    Beautifully written as always, Grace! Your hard work and tenacity in the face of the unknown (ie Python codes and invasive computer viruses) can serve as an inspiration to academics everywhere. I’m so excited that despite your roadblocks, you’ve been able to compile descriptive statistics! Following your research journey has been a real pleasure, and I can’t wait to watch you apply all of the skills that you’ve learned this summer as you continue your academic career.

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