Creating a startup while working a full time job has its pros and cons. Among the pros, you don’t have to use a lot of your time minding your investors (or looking for them), and you can devote your energies to just make the best possible product. Among the cons, progress is slower and it is very difficult to be productive on workdays, when you already spend 8 hours or more on your day job.
But a week ago I read a comment on HN (edit: thanks to raju in the comments for pointing me to the exact link) that inspired me to rethink how I’m organizing myself , and with one simple change I doubled my productivity on workdays. How? Instead of working on hashtagify at nights, after getting home from my day job, I’m starting my day two hours earlier, and doing 2 hours of programming in the morning, before going to work.
I’m usually a night person, and have always been very productive at nights, since when I was just a student. But after eight hours of work, it is difficult to have that kind of focus that you need to program, and the two (or two and a half) hours in the morning have been much more productive than the equivalent time in the evening.
After coming home I still do some lighter work, and don’t go to bed without having scheduled a task to do the next morning; this way when I wake up I don’t have to think what to do and I can be immediately productive.
So, the bottom line is that work on hashtagify pro is proceeding very well: now I’m making as much progress during the workweek as I usually make during weekends, while before I only made major progress outside workdays. This means that soon enough I’ll be able to release the first beta. Stay tuned!
If you’re doing a marketing campaign on Twitter, how can you measure its real impact? And, specifically, how can you evaluate the individual contribution of single campaign participants?
This is something that has been asked to us, and we think we’ve found an interesting solution to visually show this information by leveraging the hashtagify technology. So, if you’re interested in this kind of analysis, stay tuned. And, if you have specific suggestions or requests related to this, don’t hesitate to contact me writing to @hashtagify . First come, first served…
Be seeing you!
Hashtags were introduced to Twitter exactly 4 years ago by Chris Messina. Happy birthday to the Twitter hashtag and many thanks to Chris
Note: http://t.co/Zf6X4U5 is nothing else than hashtagify.me Thanks for the appreciation!
Did you even wonder who the top influencer about the #debt crisis is on Twitter? Is it a Republican? A Democrat? An independent – maybe an official news source?
I did, and to answer that question – and countless more about other hashtags – I just published on hashtagify.me the first beta version of a new “top influencers” feature.
With this feature, when you visually explore Twitter hashtags, following their relationships, you can also see up to 6 of the top influencers for the selected hashtag. These users are listed by name, ranked by their estimated influence, and shown on a graph where you can also see their relative influence (y-position), how specialized they are on that hashtag (x-position), and how many followers they have (bubble size).
This feature is still in beta and the hashtags usage data is still being collected: This means that, especially for the less used hashtags, the influence estimate isn’t very precise. Still, while I’m working on augmenting the data collection rate for this kind of data, you can already get an idea about the influencers on your topics of interest. And a similar feature is in the works about the top websites for an hashtag: Stay tuned!
Oh, and by the way: It looks like the top influencer about #debt is @MikeBloomberg, the Republican mayor of New York, followed by @WestWingReport, an independent White House journalist – you can see it for yourself here. Where are the Dems??
These days I’ve been working on getting the data needed to show the top tweeters/influencers for an hashtag.
For the less used hashtags that’s not easy, but for the more common ones I was already getting some interesting enough data and I was thinking about the possibility to publish a first beta this weekend.
Unfortunately, while working on this new feature, something got corrupted on Redis – the database where we collect our data – and had to go back to an older backup; you might already have noticed that the number of examined tweets displayed on hashtagify fell from over 50 to 43 millions.
Nothing serious, but this means that we’ll need to wait some more time for the first beta. I just hope to be able to publish something before I’ll leave for a 2 weeks vacation to Russia next week… but don’t hold your breath!
While working no this I also learned something interesting about how to execute batch jobs on node.js: I expected some complications from the non sequential nature of node, but I hadn’t forseen the full extent of the surprises! I’ll try to share this to thos interested in this kind of technical details an upcoming post.
The poll we ran about which features I should add first to hashtagify closed today, and the winner is… “Find top tweeters/influencers for an hashtag” (49% of votes).
I wanted to thank everybody who voted for the poll, and add that I’ve already started thinking about how to implement this new feature. I’d like to show this information in a highly visual and usable way, and I have some interesting ideas about that.
Gathering significant users’ data for the more than 1 million hashtags already categorized by hashtagify will be a real challenge, but at least for the most used ones I expect to be able to have something useful in a few weeks.
I’ll keep you posted about the developments. In the meantime, if you have suggestions or related requests feel free to post them here or to write on twitter @hashtagify
Have a great weekend. Cheers!
infosthetics.com has been as fast as light: The same day of first public release of hashtagify.me, they published a featured article about it. Thanks!