Learning the Game – Tracking My Influence On Twitter

Posted on by Zachary Schweikert

1. Influence

Over 90 or so days of measuring, my Twitter followers grew a modest 19.7%, from 66 in late August to 79 at the end of November. So what helped in terms of engagement and getting followers? It’s hard to say. Including media in my tweets, and original work at that, certainly seemed to help over tweets that were solely text-based. Engaging Twitter users with a high follower count worked on some occasions, and not others. A tweet at Dave Weasel, who runs a comedy account, garnered 2 retweets and 25 likes. A tweet directed at Tim Nudd, the creative editor at Adweek got nothing. However, I think engaging with @DaveWeasel certainly helped my number for the month of October, when I received 12 new followers and 15.1K tweet impressions (compared to 3,941 in September and 6,275 in November). Going forward, I will definitely try to engage my most influential followers.

My Klout Score experienced much greater growth at 363.65% in the 90 day period, from 11.83 to 56.65. According to Klout’s percentages, this increase in my Klout Score had more to do with my Facebook and Instagram activity than tweeting. Nonetheless, I am happy to see my Klout numbers increasing.

 

2. Execution

I consider the following ten tweets to be my best of the semester, for both their content and levels of engagement. They are arranged by date published.

Impressions: 405 | Total Engagements: 94

GIFs are hugely popular, so I’m not surprised this tweet got as many likes as it did. In executing this GIF, I played with the idea of changing an object in every frame, in a manner similar to stop-motion animation. Tagging my roommate in the post also helped in terms of impressions.

Impressions: 636 | Total Engagements: 174

Another stop-motion inspired effort, this short video also performed well, probably because it was a little weird. Off-kilter stuff thrives online. The three retweets of this video also helped with impressions.

Impressions: 376 | Total Engagements: 38

Tasked with uploading two pictures into one tweet, I decided to do a “before and after” piece. Using #cuse and #dormlife certainly helped to make this tweet more relatable to SU students or students in general.

Impressions: 12,151 | Total Engagements: 1,432

This tweet, while not really anything exciting in terms of content was exciting in terms of engagements and impressions. I found my follower with the highest influence, and targeted a tweet at him discussing his content critical of Donald Trump. With 253K followers, @DaveWeasel proved to be a good influencer to target, as it turned an ordinary tweet into my best performing one.

 

Impressions: 197 | Total Engagements: 14

While this tweet didn’t have any rockstar engagement levels, I enjoyed using Google Ngram to make a graphic on the fly.

Impressions: 274 | Total Engagements: 14

While votes were pretty low, I think I used to poll function in a creative way to celebrate the music of the Ramones. Perhaps it was too much of an in-joke, but I find this kind of use for Twitter polls to be more fun and practical – expecting to do real research with the poll function is obviously quite flawed.

Impressions: 350 | Total Engagements: 24

This tweet performed a lot better than I would have expected, but I think the “life-hack” style (and that awesome GIF) had much to do with it’s engagement numbers.

Impressions: 194 | Total Engagements: 27

I’m not one to take selfies, but I’m one to make bad puns. I enjoy the internet weirdness of this post, and tried to engage people through that.

Impressions: 263 | Total Engagements: 28

Tasked with sharing something about positivity, I chose to take it in the direction of self-deprecating positivity. I think this post performed well because it is a sort of “TBT” post. People often enjoy seeing their friends and colleagues as young kids.

 

Impressions: 134 | Total Engagements: 12

Another example of making a graphic on the fly with Snapchat. I think my use of a restroom sign was surprising and interesting, and it certainly touched on the early November feeling that winter is just around the corner. I think the timing of this post helped with it’s engagement, but it could have been more effective if tweeted later in November or early December.

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