After the initial analysis that included the basic network stats like centrality indices or network density, we took a more detailed look at the social network data. Our first interest was how often our advertisement Tweet was retweeted. We used the Twitter API to get a list of Twitter users that retweeted:
In this case, the Tweet was retweeted at least 100 times over (Twitter does not provide detailed information on the exact number), which we believe is quite a success for us . We took a first sample of the Twitter users that retweeted the Tweet from meghannz96. Surprisingly, none of the sampled Twitter users could be found in the follower network of meghannz96. We will elaborate on this and check, if we can find a overlay. We also looked for communities and we found six different communities (denoted by different colors) as shown below.
Finally, we checked the impact of the Tweets on our downloads: after the Tweets were published, we noticed an increase of downloads to 35 downloads per day. Previously, we had between 15 and 20 downloads per day. The traffic on our Web page also increased and increased to 903 hits for the product Web page http://www.ikangai.com//apps/qlauncher/ that was included in the advertisement Tweets. This is very interesting, since we had virtually no hits for this particular Web page in the months before and the advertisement Tweets have apparently a considerable impact.
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