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Recipe: Issue Profiling

Issue profiling is concerned with the distribution of issues across spheres, platforms and devices. Or: How are issues addressed across platforms and spheres. It is interested in the specific processes of issuefication, how live or current the issue is across different spaces and how lively or dynamic its negotiation is. Following this objective, it makes use of the specific activities and features of devices and platforms. Issue profiling is an attempt to trace the specificity of the issue and its happening relating to issue activities, actors and spaces.

There are different routes to take when profiling an issue, one is to compare is occurrence across different spheres and platforms, an approach which can entail cross-platform or cross-spherical analysis. A different route takes the specificity of platforms into account. The proliferation of activities enabled by social media platforms offer the possibility to profile issues through platform specific analysis, inquiring which user activities are performed within one platform, as for instance Facebook or Google+. Such platform specific analysis can be performed one a single issue, but can also be used for comparative issue analysis, putting activities of a series of issues into relation to each other. The increasing presence of platform features outside the platforms themselves, most notably through social buttons or plugins as the tweet, like or share buttons now available on the web, you might also consider platform activities performed on objects outside of the platforms themselves.
Tactics-01.png Issue Action Formats, Liveness and Liveliness
Cases-01.png Pace Online, Web Currencies
Tools-01.png Twitter Scraper, Like Scraper, Dorling Map Generator, Bubble Line tool


Cross-platform profiling

Identify relevant platforms and web spheres for analysis and determine the specific activities for each platform. Remember that each platform or sphere allows for specific activities and might need specific queries to delineate the issue. Before selecting the final queries, test a number of different ones and compare the fit of the results. Especially names of recurring events might produce results referring the previous instances of this event.

Examples are:
Twitter: Tweets for selected key words or hash-tags
Facebook: Public status updates containing key word, changes in group/page membership.
Google Web/News/Blogs: Search results related to a specific query.
Flickr: New pictures tagged with a specific term or added to issue related groups.
Youtube: New videos containing search term in title, description or tags.
Wikipedia: Edits in selected article.

Determine how the data will be retrieved from the platforms by selecting related scrapers or adjusting existing tools to build custom scripts.

Related case studies


Platform specific profiling

An alternative route is to focus on the activities an issue enacts on specific platforms. This route can entail the analysis how web content related to an issue is taken up through platform specific activities or how content of a specific issue network is being acted upon in social media.

For this approach, you need to delineate the content source set first. One possibility is to focus on Google Web/News/Blog results relating to specific issue queries.

Retrieve a set of URLs which in a second step be tested for platform engagement. A number of social media analytic tools allow to explore the number of tweets, diggs, likes or shares a website has received.

Most platform activities performed on URLS can be directly obtained via the platform API, as in the case of Facebook, which provides all likes, comments, shares and internal clicks on a website:
Or in the case of Twitter:
Such analytical approaches can be repurposed to build custom scripts allowing for batch queries of a list of URLs, as the Like Scraper.


Snapshot or dynamics over time?

Select if the analysis shall address a specific temporal interval or should function as static snap shot.

If an interval is chosen, determine how data can be retrieved for that interval, for instance be scheduling repeated scraping iterations in selected sub-intervals.


Visualise activity specific to platforms and/or according to the chosen temporal interval.

You can draw on proportionate forms of visualisation such as Dorling Maps for snap shorts of issue profiles or develop custom build visualisations showing the intensity of platform specific actions over time.




Issue profiling provides insights into to the relative issue activities across or within spheres and profiles. At allows to map out the intensity and occurrence of issues across the web and allows to inquire into processes of issuefication.

The analysis can explore the issue-specific activity profiles across platforms, i.e. if issue related content is predominantly shared or commented upon. But it can also determine fluctuations in the flow of issue related activities.


Topic revision: r3 - 14 May 2012 - 22:49:27 - CarolinGerlitz