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#ThisIsNotNormal
How a Moment Created a Movement
What is #ThisIsNotNormal?
• Stemmed from the shock of events which followed the inauguration of DT
 Themes evident in word cloud
• Movement to denounce DT’s presidency and remind people that the changes
occurring should concern them
 Sexism and Islamophobia in the White House
 Ties to Russia excused
 Inexperience of people being put in important positions
• Seems to have stemmed from moments of shock when different stories
broke; has turned into a catchphrase used in resistance to the
administration, to Islamophobia, to sexism, to DT’s ties to Russia
Word Cloud
These are the words that come up
most often in tweets with the
hashtag #ThisIsNotNormal. Many
relate to the Muslim Ban, Steve
Bannon, Russia, and “The
Resistance.”
Popular hashtags: #Bannon,
#StopPresidentBannon, #Resist,
#TheResistance, #Putin, #NSC
These all represent events and
pieces of news which have been
pieced together by a hashtag,
therefore creating a movement.
The different pieces have been
linked by the phrase, which has
become part of the terminology of
this “resistance” which had begun.
Social Network Analysis
Ran for 10 minutes Ran for 1 hour
Linking Findings to Course Material
• Based on the Kate Crawford reading, I do not have big data.
 However, does this mean it won’t be useful?
 In this case, I’m not sure how useful my data is without being combined with other
data.
• Looking at the word cloud, we could determine useful terms to study in
conjunction with #ThisIsNotNormal.
• Looking at the SNA, we could look at the different activists and
organizations with their own separate networks and try to link those
networks with other hashtags.
• Also, thinking about the Filter Bubble might provide insight on why these
networks didn’t link up more, or perhaps why this movement was not more
sustained.
Conclusion & Future Implications
• Overall, this moment of reaction to DT’s presidency and first actions led to a
larger movement on Twitter to remind people that this is NOT normal.
• Questions For the Future
 Will this theme that DT’s presidency is “not normal” continue, or was it just an
initial reaction?
 Is this “resistance” sustainable? (thinking about who is involved, the networks we
have observed, the themes around which #ThisIsNotNormal is centered)
 Without big data, how can we use the data collected from #ThisIsNotNormal with
data from other hashtags to put together a broader story?
 Comparison to #AlternativeFacts and #FakeNews
 Compare to #Resist, #Resistance, #The Resistance? Also too broad? Would have to see.
Works Cited
boyd, danah and Kate Crawford. 2012. “Critical Questions for Big Data.” Information, Communication & Society 15 (2):
662-79.
Baer, Drake. ‘The ‘Filter Bubble’ Explains Why Trump Won and You Didn’t See It Coming.” Science of US. NY Mag,
2017. http://nymag.com/scienceofus/2016/11/how-facebook-and-the-filter-bubble-pushed-trump-to-victory.html

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#ThisIsNotNormal

  • 1. #ThisIsNotNormal How a Moment Created a Movement
  • 2. What is #ThisIsNotNormal? • Stemmed from the shock of events which followed the inauguration of DT  Themes evident in word cloud • Movement to denounce DT’s presidency and remind people that the changes occurring should concern them  Sexism and Islamophobia in the White House  Ties to Russia excused  Inexperience of people being put in important positions • Seems to have stemmed from moments of shock when different stories broke; has turned into a catchphrase used in resistance to the administration, to Islamophobia, to sexism, to DT’s ties to Russia
  • 3. Word Cloud These are the words that come up most often in tweets with the hashtag #ThisIsNotNormal. Many relate to the Muslim Ban, Steve Bannon, Russia, and “The Resistance.” Popular hashtags: #Bannon, #StopPresidentBannon, #Resist, #TheResistance, #Putin, #NSC These all represent events and pieces of news which have been pieced together by a hashtag, therefore creating a movement. The different pieces have been linked by the phrase, which has become part of the terminology of this “resistance” which had begun.
  • 4. Social Network Analysis Ran for 10 minutes Ran for 1 hour
  • 5. Linking Findings to Course Material • Based on the Kate Crawford reading, I do not have big data.  However, does this mean it won’t be useful?  In this case, I’m not sure how useful my data is without being combined with other data. • Looking at the word cloud, we could determine useful terms to study in conjunction with #ThisIsNotNormal. • Looking at the SNA, we could look at the different activists and organizations with their own separate networks and try to link those networks with other hashtags. • Also, thinking about the Filter Bubble might provide insight on why these networks didn’t link up more, or perhaps why this movement was not more sustained.
  • 6. Conclusion & Future Implications • Overall, this moment of reaction to DT’s presidency and first actions led to a larger movement on Twitter to remind people that this is NOT normal. • Questions For the Future  Will this theme that DT’s presidency is “not normal” continue, or was it just an initial reaction?  Is this “resistance” sustainable? (thinking about who is involved, the networks we have observed, the themes around which #ThisIsNotNormal is centered)  Without big data, how can we use the data collected from #ThisIsNotNormal with data from other hashtags to put together a broader story?  Comparison to #AlternativeFacts and #FakeNews  Compare to #Resist, #Resistance, #The Resistance? Also too broad? Would have to see. Works Cited boyd, danah and Kate Crawford. 2012. “Critical Questions for Big Data.” Information, Communication & Society 15 (2): 662-79. Baer, Drake. ‘The ‘Filter Bubble’ Explains Why Trump Won and You Didn’t See It Coming.” Science of US. NY Mag, 2017. http://nymag.com/scienceofus/2016/11/how-facebook-and-the-filter-bubble-pushed-trump-to-victory.html