Social Media Analytics (1) Klout and Algorithims
October 29, 2011 3 Comments
A short post today about analysing your social media impact.
Opinions vary about the usefulness of this, especially since the results are based on aalgorithims that we do not, as end users, have access to. Rumours abound on social media about how these algorithims work, so I would have to add this proviso when inspecting your own analysis:
- algorithims do not take full account of your influence online
- algorithims tend to downgrade your score according to the amount of contact you have with lower scored members- this can run counter to efforts to promote digital engagement, and to mentoring newer members of social networks.
- there is no accepted final evaluation technique of network influence- all we have are the products available to us online, which are subject to the above provisos.
- algorithims are, however quite fascinating. See this fantastic TED Talk by KevinSlavin:
- Klout this free service recently tweaked it’s algorithim; some users were unaffected whilst others (including me!) saw their score reduce significantly. What does that mean? Watch this video to find out:
Klout allows us to offer +K to our “influencers”, people who have contributed to our understanding of a topic of mutual interest. It shows which topics we are supposed to be influential about, although this is a bit of a standing joke- most people hae experienced some confusion the first time they are announced to be influential about, for instance popcorn, skating, or entymology, if they have only ever Tweeted about their professional interests! Mashable have developed this guide to Klout.
That’s all for this post, next time I will be looking at other ways to measure online influence including: