Sampling YouTube-Clips from Twitter

Posted on Do 12 Januar 2012 in Blog

During the electoral campaigning for the recent german federal elections in 2013, we decided not just to monitor YouTube-Clips via classical sampling techniques like keyword-searches on YouTube. Therefore, we took advantage of the cross-pollinated diffusion processes between Social Network Sites (SNS) like Facebook or - in this case - Twitter:

To gain an understanding of which YouTube-Clips are relevant in terms of political participation and discussion on Twitter, we collected Tweets which are related to the federal elections, resolved the URLS within those Tweets and - if an URL linked to a YouTube-Clip - included these Clips in our YouTube-Election sample. This method enables the early-bird detection of (likely) political YouTube-Clips and supplements the more traditional data-collection process via YouTube search terms, channel monitoring or crawling the YouTube-Network of related videoclips

Collecting political Tweets via Streaming-API

Twitter, as opposed to Facebook as a less accessible SNS in terms of crawling topics, posts and alike, became sort of a favourite toy for the social science/information science etc. To a very large extend, Twitter (comparetivly) open API's and a vast collection of tool/websites to get data out of the system may account for this affinity towards the quite small SNS - when compared to Facebook. However, although Twitter-Users might be completely un-representative, there is a potential of Twitter as an early-warning system, ifnluential intra- media-agenda-setting authority. When dealing with the dissemination of (political) content, we can show that news-articles disseminate lamost an order of magnitude faster on Twitter than on Facebook.

Therefore, we conclude that Twitter is sort of a news-ticker, while Facebook is used for the discussion of links and content within smaller 'personal publics'. This holds true for the diffusion of audiovisual-content as well: Tweets for YouTube-Clips usually precede the Shares, Likes and Comments on Facebook (see one example above).

What´s crucial here and should not be underestimated is the flow of content not only within SNS, but across different online-outlets. These cross- pollination process might be triggered by users who uses both multiple networks and once (Studies?) and disseminate content/links - like bee's transport pollen - into other networks. Of course, users who do create content on platforms like YouTube tend to use Twitter and Facebook (Study) and therefore pollute other SNS intentionally (which links to the concept of virality ..). From a more abstract, system-theoretical viewpoint, social or communicative subsystems like Twitter and Facebook observe and react to each other (again, Twitter is more observable than Facebook, f.e.).