Lab 2- Mapping illustrated how large cities within the United States are most active on twitter. We all had tweets focused in the United States. This shows how all of our issues of transgender, Planned Parenthood, and LGBT are focused in United States. This map wasn’t as helpful as the others for me as not much of my data contained mappable tweets.<\/p>\n
Lab 3- text analysis was very interesting for all of our labs. Seeing the most important words within our data sets was very interesting. For my own word web, the most prominent word was Naty’s hashtag transgender. This illustrated how all of our hashtags overlapped and how LGBT acts as an umbrella for L B G and T members, and all of them have a strong voice. Also, the words trending day by day showed how people’s emotions get involved on twitter. I tracked the day’s before and after Trump’s decision against transgender bathrooms and it is interesting to see how current events effect people’s emotions.<\/p>\n
Lab 4-Graphing was the most interesting\u00a0of my data visualizations. My Giphy was unlike Jill’s and Naty’s. Everyone was involved in the same conversation. Where Naty and Jill had individual user’s dominate the conversation, mine was relatively equal. This showed how my hashtag LGBT was more of a community than a facilitated conversation where a few accounts on twitter were dominating the conversation.<\/p>\n
Lab 5- Language and day by day breakdown. This lab helped me realize how predominate my topic is in the United States. A lot of my tweets were in english. Also, this made me solidify the fact that current events and popular culture events dominate member of the LGBT community’s conversations on twitter. After the day by day breakdown, I noticed that popular days where there were a lot of tweets often correlates to things like The Oscars, or nights of show’s premiering.<\/p>\n
<\/p>\n
For my final presentation I plan on displaying my data visualization from lab 4, where it illustrated how LGBT hashtag is a community.<\/p>\n
I also want to show my day by day tweets and how it correlates to the days of the Oscars etc.<\/p>\n
this would like to the data vis from lab four because one of the main users are often TV show promoters.<\/p>\n
I think that this display would flow nicely with the trending words by day by day to illustrate how emotions and current events effect the amount of tweets per day.<\/p>\n
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