{"action":"opened","issue":{"url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/issues/523","repository_url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016","labels_url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/issues/523/labels{/name}","comments_url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/issues/523/comments","events_url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/issues/523/events","html_url":"https://github.com/MozillaFoundation/mozfest-program-2016/issues/523","id":168612827,"number":523,"title":"Connecting the Dots: Network Analysis for Organisational Value","user":{"login":"mozfest-bot","id":19719869,"avatar_url":"https://avatars.githubusercontent.com/u/19719869?v=3","gravatar_id":"","url":"https://api.github.com/users/mozfest-bot","html_url":"https://github.com/mozfest-bot","followers_url":"https://api.github.com/users/mozfest-bot/followers","following_url":"https://api.github.com/users/mozfest-bot/following{/other_user}","gists_url":"https://api.github.com/users/mozfest-bot/gists{/gist_id}","starred_url":"https://api.github.com/users/mozfest-bot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mozfest-bot/subscriptions","organizations_url":"https://api.github.com/users/mozfest-bot/orgs","repos_url":"https://api.github.com/users/mozfest-bot/repos","events_url":"https://api.github.com/users/mozfest-bot/events{/privacy}","received_events_url":"https://api.github.com/users/mozfest-bot/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/labels/[Space]%20Journalism","name":"[Space] Journalism","color":"006b75"},{"url":"https://api.github.com/repos/MozillaFoundation/mozfest-program-2016/labels/[Space]%20Open%20science","name":"[Space] Open science","color":"d4c5f9"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-08-01T10:16:21Z","updated_at":"2016-08-01T10:16:21Z","closed_at":null,"body":"**[ ID ]** 650e9fbe-334e-4711-9233-e0a414c39d98\n\n**[ Submitter's Name ]** Caitlin McDonald\n**[ Submitter's Affiliated Organisation ]** TES Global\n**[ Submitter's Twitter ]** @caitiewrites\n\n**[ Space ]** science\n**[ Secondary Space ]** journalism\n\n\n\n\n**[ Format ]** learning-lab, fireside\n\n### Description\nParticipants will leave the session with an understanding of what network evaluation is, why organisations (both commercial and non-commercial) care about network evaluation, and different methodological approaches to collecting and processing data for network analysis.  Parts of the session will be suitable for people with little to no experience in network evaluation; other parts will be geared more towards people with an existing knowledge of these principles who are focused on learning from people with pragmatic experience in running programmes for network evaluation.\n\n### Agenda\nArliss (or other Mozilla analysts) and I will present information about what network analysis is, why it’s important to our respective organisations, and how we conducted our organisations’ first experiments with network mapping in spring/summer 2016.  We may also do simple demos of network analysis, either using appropriately anonymised demo data we’ve prepared or publically available tools such as the Neo4j Twitter graph demo (where users can enter their own information): http://network.graphdemos.com/\n\n\n### Participants\nWith a small amount of participants we might be able to increase discussion time and talk about specific challenges faced by groups or individuals which have different data or methods available to them, and how to specifically approach those challenges.  With a larger group we could run through the examples of our respective network mapping experiments and focus on generalising these principles.\n\n\n\n### Outcome\nParticipants should leave the session with a basic understanding of what network evaluation is and why it is important to a range of organisations, as well as a toolkit of further resources to help their own efforts in network analysis.  They should also be familiar with some of the challenges for data collection and manipulation for network analysis methods.\n\n"}}
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