In this paper the influence of interventions on Twitter users is studied. We define influence in a) number of participants, b) size of the audience, c) amount of activity, and d) reach. Influence is studied for four different target groups: a) politicians, b) journalists, c) employees and d) the general public. Furthermore, two types of interventions are studied: a) by all Twitter users (i.e., uncontrolled interventions), and b) those tweeted by an organization that benefits from any resulting influence (i.e., controlled interventions). As a case study, tweets about a large Dutch governmental organization are used.

The Automatic Content Linking Device monitors a conversation and uses automatically recognized words to retrieve documents that are of potential use to the participants. The document set includes project related reports or emails, transcribed snippets of past meetings, and websites. Retrieval results are displayed at regular intervals.

We present an approach to global transaction management in workflow environments. The transaction mechanism is based on the well-known notion of sagas, but extended to deal with arbitrary process structures including cycles and savepoints that allow partial compensation. We present a formal specification of the transaction model and transaction management mechanisms in set and graph theory, providing clear, unambiguous transaction semantics. The specification is straightforwardly mapped to a modular architecture, the implementation of which is applied in the prototype of a commercial workflow management system. The loosely-coupled nature of the resulting system allows easy distribution using middleware technology.