The Influence of #AlanRickman’s Death in the Twitter World

Alan Rickman, an English actor and director and important part in the extremely influential Harry Potter series passed away on January 14th, 2016 due to pancreatic cancer at the age of 69. Most known for his role as Severus Snape in the Harry Potter films, his death was truly upsetting to the large Harry Potter fan base. He was mourned worldwide across social media platforms, from the morning of January 14th through the weeks following.

Overall latest activity: 

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How many mentions globally? 741,191 Total mentions occurred over social media using the hashtag #AlanRickman to mourn his death. The majority of the conversation took place on Twitter (739,953), and other outlets included blogs (210), forums (222), and the news (806).

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What reach did his death have? Given that Alan Rickman has been acting since the 1980s, and peaked in his stardom acting in the Harry Potter series that has immense global influence. The United States made up 27.2% of all conversations, followed by the United Kingdom (12.2%), France with 6.6%, and Mexico with 3.7%. As the country distribution chart below shows people across the world were tweeting in honor of him.

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What were people saying? Looking at the buzz graph and word cloud generated by the conversations had on the days around his death, the data shows, most people discussing his life and mourning the loss with the appearance of words like “saddened” and “tribute.”

People also mentioned his costars such as “emma watson,” “radcliff,” and the character he played “snape.”

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The data also shows that the most retweeted tweet was on from one of his costars in the Harry Potter series, Emma Watson, further showing the love and respect he had in the Harry Potter realm.

Sami Meyerson, Bari Bressman, Esther Xu

 

One thought on “The Influence of #AlanRickman’s Death in the Twitter World

  1. When I was using sysmos, the big “https” appears all the time in keywords no matter what object I was analyzing. Wondering is there any way to avoid that or is there any keyword analyzing tool can avoid that.

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