After reading\u00a0Text Analysis and Visualization: Making Meaning Count,<\/em> by Stefan Sinclair and Geoffrey Rockwell, I was forced to realize that racial stereotypes still do exist in professional sports. We’ve as a country and society come a long way since the 50s and 60s, but we still have a long way to go. Relating specifically to the article, in a study performed on NFL players they found that, “white players were more likely to be called \u201cintelligent\u201d and blacks more likely to be called \u201cnatural”.\u201d This doesn’t come as a huge surprise considering the recent events in the NFL involving quarterback Colin Kaepernick. Kaepernick, with both the IQ and athleticism to be an elite quarterback in the league, still has yet to be signed because he publicly expressed his disgust in the current state of the league.\u00a0 Relating this back to text analysis, studies like the one in the article are easy to conduct, but are they completely relevant and accurate in their findings. For example, is there an even split in white vs. black players in the NFL. I would guess absolutely not. This makes it very difficult to compare frequency of certain words like natural and intelligent.<\/p>\n

MLC makes some good points in her article about the potential biases that come about with this type of analysis. The author says, “Looking at the frequency of times particular words are mentioned can uncover some bias, which may be unnoticeable at a readthrough.” I would like to do some further research on the particular NFL study conducted to see if I could uncover some biases.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

After reading Text Analysis and Visualization: Making Meaning Count, by Stefan Sinclair and Geoffrey Rockwell, I was forced to realize that racial stereotypes still do exist in professional sports. We’ve as a country and society come a long way since the 50s and 60s, but we still have a long way to go. Relating specifically to … <\/p>\n

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