Taking a look back at the compilation of data visualizations that I have created over the course of this semester I start to understand more of the meaning behind my hashtag, #FakeNews. Then I take a look at the data visualizations created by those members in my group that analyze a different hashtag and start to understand the disparities among them. For example, Michaella has the hashtag #ThisIsNotNormal which coincides with mine in a way. The reason I say this is because it seems that the United States is in its own world when it comes to the awareness of the current political climate which results in uneducated gestures by our own people. In terms of our hashtags, people have the freedom to label any acts by the administration as abnormal or as fake news and this is where things become interesting. This is not normal seems to be a more educationally backed hashtag given that there have been major spikes in the frequency of the tweets when there was an executive order given that was, in fact, NOT normal– for example, the Muslim ban. When you seek to note trends in my data, there are random spikes whenever there is any sort of press about an individual whether its aligned with the people’s views or not. In conclusion, I would say that is more common understanding for even supporters of the Muslim ban to know that it is not normal, but whenever a viewer disagrees with a press release of some sort, it seems they label it fake news.
I believe then that the strongest form of analysis for my hashtag would be tweets by day, considering it evidently shows the trends as major events and even minor events occur within our country, and also “tweets by language”. I believe that tweets by language is important because it highlights multiple dynamics that I claim to be significant. First, all of this obsession around fake news is mainly in the United States. We have developed a system that has given power to the media in the form of persuasion. This is evidenced in the lack of cleanliness displayed in the presidential campaign by both parties. Without personal connection, it is impossible to understand the reality of situation without its real-time context. This provides leverage to the media by giving liberty to the people to interpret their stories in whichever way they feel, while still forcing the setting in which their interpretation should fit. I think this final presentation is a knock on the United States and the current climate which points fingers every which way when failing to resolve our issues.
Outline:
Title Slide: #FakeNews
Background: What is Fake News? How did it get its name? Who reinforced it?
Data Visualization #1: Tweets by Day
Data Visualization #2: Tweets by Language
Readings: Kate Crawford
Summary: What does this all mean? What does it matter? Cite.
It is really cool to see how your tweets change with the days and the languages. The connection between the two is great! Your powerpoint looks strong and I am looking forward to seeing the final product.
I like how you interpret the whole “this is not normal” idea to support your own data- it has definitely given me some insight. I also really like your analysis of the media and your final thought that everyone is really just pointing fingers. Looking forward to your presentation.
The graphs you chose are very interesting but what #fakenews issues came up on certain days and why, per your text analysis? It’s vague to say it changes daily if you don’t have evidence and examples to back it up. Dig in farther. Finally, what will the Crawford reading do you for hear in regards to thinking through filter bubbles? Does your hashtag fight back against filter bubbles or produce new ones?