The #ThisIsNotNormal movement stemmed from shock and concern over events following Donald Trump's inauguration as president, including sexism and Islamophobia in the White House, ties to Russia, and inexperienced appointments. The hashtag was used to resist these issues and the administration. Word clouds and social network analysis of tweets showed the hashtag linked to other popular issues and groups. While the data is limited, it provides insight into how the reaction formed a sustained online movement of resistance through connecting different issues. Questions remain around whether this theme of an "abnormal" presidency will continue and if the networks can sustain the movement.

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