“But how?” – A discussion sparked between me and another Web Ecologist  – Railsbob. We were aiming to see if we could devise a way such that more people get to know about WebCoherence using Twitter’s platform and to setup an experiment around it. After going through a lot of Twitter updates Railsbob observed that users were using hashtags to communicate in a larger community. RailsBob suggested: ” If we use a relevant ‘#keyword’ as a  hashtag, we could possibly attract more users to our site via Twitter.”

“Interesting,” I exclaimed, “but where do we find the relevant hashtags?” “It is not like the #communia conference, which some of our colleagues attended. They had a ready-made shared keyword. We don’t.” Back to the drawing board!

RailsBob then suggested using the #hashtags database on www.hashtags.org to search for relevant Twitter #hashtags. Eureka! We now had a list of the most popular hashtags. We would use only those we found to be appropriate from among the most popular ones (namely listed at the top), and this would save hunting through the whole of what is a huge database. After all there was nothing to lose – the worst that could happen is that we remained unnoticed. As Web Ecologists, we were now ready to test the idea. We took top 5 hashtags from the database list and sent out tweets publicizing WebCoherence. We waited for 3 days to collect sufficient Google Analytics Reports and here is what we found.

The Results:
1. In less than 24 hours 12 more followers started following WebCoherence on Twitter! And in 3 days now the count has risen to 53 followers. A staggering growth of 430% in three days from an initial count of 10 followers.
2. Google analytics report shows 19 hits came to the website with the referring URL Twitter.com. The number of hits were quite less as compared to the number of followers who started following WebCoherence.org.
3. Interestingly, no comments were received from new followers.

This brings us more mysteries that need to be solved before we come to any further conclusions. We are now left with various questions:

Do users follow on Twitter just to increase their follow count?
How do users interact when they receive links to external websites on Twitter?
Why do users want to increase their follow count if they are not interested in reading Twitter messages?

We intend to reveal answers to these questions in our upcoming posts as we analyse results and make more observations, keep watching!

P.S.: If you have seen some odd behavior and if you wish to contribute by experimenting with WebCoherence, do get in touch with us by leaving comments to this post or by emailing us. Thanks in advance!

Aim: To check the nature and amount of spam received when email addresses are left on the public world wide web.

Ingredients: Email addresses set up with popular ISPs (Google and Hotmail), and access to a public web page.

Method:

Step 1 : Create two email addresses, one each on Google and Hotmail using the techniques listed at the following link. (Experimenters might also choose to create one email address rather than two.)

http://webcoherence.org/2009/03/17/email-experiments-starting-simply/

Step 2 : Setup all emails from these email addresses so they will be forwarded to us, so that we can periodically analyze the emails received every week, and keep you updated with our results on the blog.

Google email address should be forwarded to: coherence.experiment1@googlemail.com


Hotmail email address should be forwarded to: coherence.experiment1@hotmail.co.uk

The steps to forward emails for Google and Hotmail can be found at the following link:

http://webcoherence.org/2009/03/23/email-experiments-setting-up-forwarding/

Step 3 : Post these newly created email addresses as comments to this post. This has the effect of making these email addresses available on the public World Wide Web.

Once you post the email addresses as comments to this post, we shall start monitoring our mailboxes for the spam emails that will be forwarded from these newly created email accounts and update the results on our blog.

Step 4 : Do not use these email addresses elsewhere, or for other experiments.

Observation:

We shall be posting our observations as we analyze spam emails from your accounts.

Expected Results:

Web Crawlers will pick up live email addresses, and use them to spam mailboxes.

Conclusion:

The conclusion will be posted after sufficient observations have been made over a period of time.

Note:

Experimenters and other audiences are encouraged to discuss this experiment using the comment box below.