Of all the low-hanging fruit in the journalistic world, the social media reaction story has to be one of the easiest to write. It’s pretty simple: all you do is look at social media after a major event and see what people are saying. Then, you write it down. Then you publish what you wrote. Voila! Journalism prêt a porter!
Some recent examples you will find all over the Web include social media reactions to the selection of a new Pope; to Justin Bieber fainting on stage; to the Oscars; to the Super Bowl; to a new Apple product; to a grumpy cat… really, to anything at all. Better yet, the focus of the social media reaction story can range from international (e.g., bloggers in China) to local (e.g., Twitter users in the central Susquehanna valley region). And best of all, you can also write about people reacting on social media to other people’s social media reactions, and the reactions to their reactions, and so on.
To make it even easier for any aspiring social media columnists out there, I have worked up a general outline with some useful phrases and a can’t-fail structure as an all-purpose guide for social media reaction stories. Just fill in the blanks with nouns or phrases describing the relevant event, and you’re done!
Social Media Reacts to ____
The social media world reacted with a wide range of responses to the ____ today, reflecting the huge interest around the (county/state/country/world) in _____ -- not to mention the democratizing effect of social media, which allows everyone to share their opinion. In the first 24 hours alone, Twitter counted _#_ tweets and Facebook tallied _#_ posts about the news. For a few hours the top-trending hashtag on Twitter was ____.
Many social media users were taken by surprise. One Twitter user, @____, registered shock at the news: “OMG!!! ______.” Meanwhile Facebook user ____ opined: “OMG!!! _______. LOL.” After the shock wore off, many social media users expressed support for _____. Twitter user @____ reflected: “_____. It’s about time!!!”
Indeed ____, the founder and CEO of social measurement platform ____, said the company’s sentiment analysis showed the reaction was mostly positive, with ___% approving and just ___% disapproving (the company’s sophisticated sentiment analysis engine relies on natural language processing to deduce sentiment from words and phrases like “good,” “bad,” “great,” “happy,” “son of a bitch,” “celebrate,” and “bastard”).
But as that latter figure indicates, not everyone was happy with the news: one Twitter user, @____, summed up his feelings with a profanity-laced tweet which read in part, “To hell with ____ I’m gettin f-ed up tonight ha ha LOL YOLO.” Following over 100,000 hostile comments, the Twitter account was deleted a few hours later.
In typical social media fashion, some people were just out to have fun. Before the end of the night, pranksters had set up thirty fake ____ accounts on Twitter, the most popular of which attracted two million followers in a few hours. Not everyone was in on the joke, however: a number of news stories citing the fake accounts were later retracted by embarrassed news organizations. One news provider, ____, confessed “We can’t tell what’s real and what’s fake anymore. It’s all a meaningless blur. Please put us out of our misery.”