About TweetLevel
TweetLevel is a Twitter measurement tool created by @jonnybentwood, @alexparish at Edelman
This tool is still in beta. Even though we believe that it goes a great way to understand and quantify the varying importance of different people's usage of Twitter, by no means whatsoever do we believe we have fully solved the 'influence' problem. What we would appreciate is your views, your feedback, advice and criticism is crucial in helping us understand social media measurement.
TweetLevel's Methodology
| Fo |
Number of followers |
Fg |
Number users following |
| Up |
Number of updates |
@U |
Number of name pointing |
| Rt |
Number of retweets |
Ta |
Twitalyzer score |
| TaN:S |
Twitalyzer noise to signal ratio |
Ti |
Twinfluence score |
| Tg |
Twittergrader score |
Ii |
Involvement index score |
| Vi |
Velocity index score |
w |
Weight assigned to each attribute |
| Z |
Standardised score |
p |
Popularity |
| e |
Engagement |
i |
Influence |
| t |
Trust |
Rg |
Range assigned to score |
Here's a bundle more info
Following
Twitter lists the number of people each user follows. The tendency for most celebrities is to only follow a few individuals the more people that someone follows, there is an increased likelihood of them actively participating in conversations with the community instead of simply broadcasting to it. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.
Followers
Twitter lists the number of people each user follows. Some Twitter users do not follow anyone but simply rely upon broadcasting what they have to say to all their followers. Some parts of the algorithm place a higher weighting on being engaged with a community and so following people is important but will not dramatically change someones score. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.
Updates
How often does someone update what they are doing. This number is purely objective as it scores someone highly no matter what the content of their post (i.e. how relevant is it). Nevertheless it is assumed that if someone posts frequently but has poor content then their 'followers' will decrease. Update ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm.
Name Pointing
e.g. @name How many people engage in conversation with an individual or point to their name. The clearest way to establish this is to run a search on the number of people who reference @username in a message. This calculation is based upon a combination of factors looking back 12 days, 1500 tweets and activity over the past 24 hours. The number of times this happens is calculated with each range was assigned a number (0 to 30) – again this was then used as part of the algorithm.
Retweets
Has a tweet caused sufficient interest that it is worth re-submitting by others? Despite a great deal of 'noise' (i.e. posts that are not relevant or interesting), when someone sees something that is of high interest, their post can be re-tweeted. The clearest way to establish this is to run a search on the number of people who reference RT @username in a message. This calculation is based upon a combination of factors looking back 12 days, 1500 tweets and activity over the past 24 hours. The number of times this happens is calculated with each range was assigned a number (0 to 50) - again this was then used as part of the algorithm.
Twitalyzer
"This is a unique (
and online) tool to evaluate the activity of any Twitter user and report on relative influence, signal-to-noise ratio, generosity, velocity, clout, and other useful measures of success in social media." This 3rd party tool (which has opened its’ API to TweetLevel) is a useful method to combine automated metrics dependent upon criteria within posts and publicly available numbers. Where tools such as this are available, we incorporate them into the algorithm to achieve a more confident score. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twitalyzer noise to signal ratio
Signal-to-noise ratio is a measure of the tendency for people to pass information, as opposed to anecdote. Signal can be references to other people (defined by the use of "@" followed by text), links to URLs you can visit (defined by the use of "http://" followed by text), hashtags you can explore and participate with (defined by the use of "#" followed by text), retweets of other people, passing along information (defined by the use of "rt", "r/t/", "retweet" or "via"). If you take the sum of these four elements and divide that by the number of updates published, you get the "signal to noise" ratio. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twinfluence Rank
Twinfluence is an automated 3rd party tool that uses APIs to measure influence. For example: "Imagine Twitterer1, who has 10,000 followers – most of which are bots and inactives with no followers of their own. Now imagine Twitterer2, who only has 10 followers – but each of them has 5,000 followers. Who has the most real "influence?" Twitterer2, of course." As with Twitalyzer, this index uses 3rd party tools to add greater confidence in the overall Twitter score. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twitter Grader
Twitter Grader is the final automated tool to add greater confidence to the final index. This site creates a score by evaluating a twitter profile. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Involvement Index
The Involvement Index is unique Edelman IP that calculates a score based upon how an indivdual engages with their community. It is calculated by analysing the content of an individual posts. People who score highest in this category have frequent, relevant, high-quality content that actively involved the twitter community (asking questions, posting links or commenting on discussions) and did not purely consist of broadcasting. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Velocity Index
As more people engage on Twitter, it may become harder to keep activity going. The velocity index measures changes on a regular basis and assigns a score based on increased or decreased participation. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Weighting
Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish an individual’s total score.
Weighted for Popularity
The key variable is the number of people someone has following them. There are many online tools that show this such as
Twitterholic.
Weighted for Engagement
The key variables are an individual's participation with the Twitter community (as measured by the Involvement Index), with additional emphasis on the frequency of people name pointing an individual (via @username), the numbers of followers and the signal to noise ratio. Other attributes were included in the final score but were given a lower weighting.
Weighted for Influence
The key variables in this instance is a combination of the number and authority of someone's followers together with the frequency of people name pointing an individual (via @username) and the how many times and individuals posts are re-tweeted. Other attributes were included in the final score but were given a lower weighting.
Weighted for Trust
The best measure of trust is whether an in individual is will to ‘trust’ what someone else has said sufficiently that they are also prepared to have what they tweeted associated with them. The key metric in this instance looks at combination of retweets and references (shown through 'via'. Other attributes were included in the final score but were given a lower weighting.
