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Social Influence 101

Influence; ability to drive action i.e. people responding to you sharing stuff.

In short, YOU say & share stuff about certain TOPICS through various CHANNELS, your AUDIENCE REACTS, you have INFLUENCE.

Think you get the picture.

While some companies / agencies try to gauge influence using a logarithmic scale, VALUE / REAL INFLUENCE is – as a blog post I read somewhere once suggested – is in the eye of the beholder. Yes, social influence & social capital gets talked about in and around the use of twitter, however while we still have offline media as well as its online counterpart, ‘the value’ lies in and how ‘the data’ (what’s being said) is interpreted / applied according to the likes, lovers and interests of the message receiver.

Imagine that you are trying to create a scoring system for the social influence for people in relation to a specific company. How would I go about using such a tool to solve this problem? Ah, the Datasift Query Builder tool – an excellent place to start. Using Query Builder, you can create a filter or set of filters that could be used to identify relevant conversation/content on Twitter. Though in a short space of time earlier today – started to build the query however without the API in place for me to run the query against / through, turned out to be somewhat of a fruitless exercise.

In ‘processing’ the results, I would have them scored them all on influence though, I haven’t got that far (yet).

I started to think through the algorithm, ranking engine and ‘secret sauce’ used to score such a thing - degrees of relationship between the sender / receiver, the context of engagement, the sentiment of commentary, the transient nature of the followers (average follower life) etc etc. Someone with 20,000 Twitter followers & lots of retweets as compared with someone with only 1,000 Twitter followers and a lot fewer retweets but consistent / more meaningful debate among their targeted community – how would they stack up against each other?

How that’s modelled through the Datasift Query Builder tool, need more time on it I guess.

The person must have an audience i.e. their messages have the potential to reach others although the potential reach of a message in a social network depends on several different factors; how many real “followers” (friends, fans, connections) a person has let alone when the message is posted. Back on task … perhaps I need to rule out bots / crappy twitter names as to distinguish ‘real followers’ though that’s not an easy thing to do.

Several social networks, such as Facebook and Google+ prioritize the display of posts for followers based on recent interaction between the follower and the post’s author. Suffering from ‘size anxiety’, some brands / people have opted to buy fake followers. While representing a definite NO NO in Social Media circles, how do I compensate for fakes in the secret sauce for calculating influence?

The more I read - the more words I now have to describe what I’m trying to model. “Influence”; an ability to amplify a message across social channels. For the purposes of social media marketing, influence might be defined as: the capacity to have an effect on the behaviour of someone in a way which results, directly or indirectly, in a business outcome. Not sure the second definition helps me much.

Back to the receiver … the posted message must resonate. The post must be on a topic of interest to the recipient. Is the author perceived as an authority on the topic regardless of what they’ve posted previously or does she otherwise have credibility due to a personal relationship with the recipient? Are the contents of the post timely? Something the recipient was thinking too? Is the message original? Is the message appreciated for its tone or style (use of humour, sarcasm, irony)? If the message resonates to any degree, then it will have succeeded in capturing a recipient’s attention? A message resonates if it provokes a recipient to interact with it. Typical social interactions include commenting on an update (comment, reply), endorsing an update (favourite), sharing an update (re-tweet), clicking on a shared link or maybe, playing a shared video.

Looking at Klout ‘scoring’ … your ‘True Reach’ is the number of people you influence. They filter out spam and bots and focus on the people who are acting on the content. When you post a message, these people tend to respond or share it. ‘Amplification’ is how much you influence people. When you post a message, how many people respond to it or spread it further? If people often act upon your content you have a high Amplification score. Last but not least, ‘Network Impact’ indicates the influence of the people in your True Reach. How often do top Influencers share and respond to your content? When they do so, they are increasing your Network score.

PeerIndex describes its sub-scores as … ‘Authority’; the measure of trust - calculating how much others rely on your recommendations and opinion in general and on particular topics. ‘Audience’; a normalised indication of your reach taking into account the relative size of your audience to the size of the audiences of others. In calculating your Audience Score, they do not simply use the number of people who follow you, but instead generate from the number of people who are impacted by your actions and are receptive to what you are saying. Lastly, ‘Activity Score’ is the measure of how much you do that is related to the topic communities you are part of. By being too active, your topic community members tend to get fatigued and may stop engaging with you; by taking a long hiatus on a particular topic, community members may not engage with a long absent member. Your Activity Score takes into account this behaviour.

Kred is composed of … two scores; ‘Influence’ is measured by assessing how frequently you are Retweeted, Replied, Mentioned and Followed on Twitter. If you connect your Facebook account to your Kred profile, you get Influence points when people interact with your content on your wall and the walls of others who have registered their Facebook account with Kred. Facebook interactions counted towards your Kred include Posts, Mentions, Likes, Shares and Event Invitations. Also ‘Outreach’ is measured on Twitter using your Retweets, Replies and Mentions of others. When your Facebook account is connected to your Kred profile, you get Outreach points for interactions on your own wall and the walls of others who have registered their Facebook account with Kred. Interactions counted towards Kred include Posts, Mentions, Comments and Likes. Your Outreach score is cumulative and always increases according the Kred website.

Though I’ve lost the source right now, a study from Georgia Tech challenges the notion that social media rewards those who talk too much about themselves. Instead, posting informational rather than self-expressive content contributed to the accumulation of followers. They put the case that tweeting what you had for breakfast is likely to cost you followers over time.

My breakfast breakdown is both interesting and important. I promise.

Complaining or expressing negative sentiment inhibits follower growth.

Expressing positive sentiment helps facilitate it.

Informational content beats overly personal content; simply broadcasting content is not the way to go.

Overuse of #hashtags turns would-be followers away.

Before I model all this out in a structured query on the datasift Query Builder, coffee is called for.

Then – taking it one step further – I may start gathering a list of market analysts or journalists also interested in said company.

THEN, extend the filter(s) to identify/classify Tweets from these guys / gals.

I love a challenge.