There are currently over 175 million Twitter accounts worldwide, making Twitter one of the most popular and most observed Social Media platform. But Twitter is not so much a social network where the exchange of personal information is facilitated -in fact, recent surveys state that it's not very social at all with a large amount of inactive accounts and a low motivation of engaging in dialogues [1]. Twitter has rather evolved into a pool of constantly updating information streams consisting of links, short status updates, and eyewitness news. Among the millions of users, a small percentage is what is called the group of influencers or alpha users. They have a large, active audience that consumes and multiplies the content published by the influencer. Thus, an influencer's content -whether it is plain text or links -is distributed in a number of micro-networks and receives attention from a large amount of users even though they might not even be direct followers of the influencer. The further the content is spread, the further the influence of the user reaches.There are various tools that enable performance measurement on Social Media. Some only sum up numbers such as the amount of followers or mentions gained on Twitter; others interpret the numbers and rate the performance using a specific algorithm. An example for the latter is Klout, a popular service that will be looked at more closely, focusing on the question of how Klout calculates its scores which serve as a means of measuring success of Twitter usage.The research purpose of this paper is to determine a grounded approach for measuring social networking potential of individual Twitter users.

Internet phenomena like Facebook or Twitter hold great potential for companies. The 21st century’s social networks are platforms for the (semi) public exchange of information that is produced and consumed by users alike. For an organisation, taking an active part in these conversations can support the efforts to gain more trust, co-shape the organisation’s image and obtain knowledge from user-generated content. User-generated content can help optimise processes and act as a testimonial for the organisation’s services and products. This work offers an outline of motivation for, types and use of user-generated content in Social Media and provides a conceptional process model facilitating external knowledge management within organisational communication measures in Social Media.

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