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Influence redefined.

Is it time to forget the numbers game in favour of a more meaningful measurement of our social influence and should this be service specific?

When I wrote "The 3 R's of Influence" I suggested that the true measure of influence is a combination of reach, reputation and relevance.

Reputation is closely linked to identity and has, interestingly, been touched on elsewhere with regards to the Google patent for multiple identities or pseudonyms. Relevance is obvious - people will interact more with content that is relevant to their interests and current circumstances such as time or location.

Which leaves reach

Reach is a literal figure - an idealised "potential", a social pyramid scheme.

I wrote that:

Our reach is a combination of our direct first level connections and those secondary connections exposed to our content by re-shares, retweets, etc.

The important word here is "exposed" but this is often overlooked in the quest for quantitative scores rather than qualitative.

Evan Williams, Twitter co-founder, has remarked that reach on it's own isn't enough and that, perhaps, a new statistic should be used to more accurately measure influence on Twitter such as retweets.

We know that the number of followers isn't a reliable metric and reach on its own is an incongruous statistic. Klout attempts to nulify the impact of pure numbers by examining the ratio of engagement to audience - penalising those who amass followers without also increasing engagement - but even this isn't enough.

Just because someone retweets your content and they have 1000 followers, it doesn't mean that all those 1000 followers are effectivly "reached" by your tweet.

Visibility and exposure are key here - someone can only be influenced by something if they read it which is why Williams states the dream metric "is how many people saw your tweet". This means that they must be online and have had the initial tweet or any retweets visible in their timelines whilst "active" on the service.

If a tree falls in the woods...

Measuring

Since the acquisition of Trendly we have been waiting for Twitter to roll out first-party tweet analytics but this has only materialised for advertisers. I proposed that:

influence cannot be accurately measured externally from the data source as there is a limit to what can be gleaned from what is publicly available. The service hosting the data (be it Twitter, Facebook or Google) has a better understanding of exactly what happens to that data including other factors such as link tracking.

Williams suggests that part of the reason Twitter has been aggressively policing access to the API might be to ensure that it gets better data as it has been unable to effectively measure activity due to the use of third party clients.

The introduction of the built-in t.co URL shortening service enhances the ability to track reactions to tweets. Even if a tweet does not receive any replies or retweets Twitter is able to count the number of clicks the shortened address receives and, therefore, gain an indication of its popularity. This is an ideal source of data to feed the #discover tab and could contribute to an individuals influence on the site as well as providing useful metrics for advertisers.

Twitter Cards

The rise in social curation has lead to a number of curators becoming "social stars" in their own right with large followings and high influence scores. All too often this celebrity is at the expense of the content creator as links are wrapped in increasing levels of URL shorteners with no attribution provided.

Frequently, a curators tweets are reshared by their audience without those followers even visiting the link simply due to the "reputation" of the curator. The curator's influence is increased with no reference to those creating the content.

Twitter Cards will change this.

A quick test has shown that Twitter Cards will resolve the shortened URLs and still display the card information associated with the link which includes the Twitter username of the author, potentially increasing the likelihood of the originating author being followed rather than the curator.

It remains to be seen if Twitter Cards will provide any SEO benefits but I would imagine that having the rich snippet text associated with each tweet will enhance the effect of each external back link generated in this manner.

Time for change

We cannot rely on a single system to calculate influence for all and we also cannot rely on a single score to reflect our own influence and reputation across the whole social web; moving to service specific grading may be a viable alternative.

Each service host is far better placed to measure true activity within its own walls so, while they may not disappear completely, follower numbers might only contribute to an influence score for that particular network based on a wider range of factors.

Is it time for a change?

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