“The best of Twitter in your inbox” – Thanks, but no thanks!

 #Blog2012, Breaking News, Geospatial Analysis / Mapping, Real-Time Journalism, Twitter  4 Responses »
May 152012
 

Surely you’ve seen this: I got one of those emails. As far as I’m concerned it’s spam and I’ll be disabling it.It is not

  • Timely – what good is a summary of last week’s tweets?
  • Revelant – I don’t see any evidence that it tracks the topics I care about. And, of course, if I did care about a topic, I’d be tracking it on Twitter via search, in my RSS feed reader, via search engines, on email lists and even in face-to-face meetings.
  • Personal – It’s a damn email autoresponder, fercryingoutloud! Sure, it knows my name and Twitter handle, just like every other email autoresponder I’ve ever joined.

I think this is a giant leap backwards for Twitter. Email marketing represents everything a lot of us hate about the Internet. It’s annoying and for the most part a waste of the senders’ time as well as the receivers. I’m on probably a dozen or two email lists / Google Groups relevant to my interests. But I rarely give out my email address any more to, say, download a “free white paper” or some other “content marketing” gizmo.

Twitter has an email list of hundreds of millions of addresses. How long do you suppose it will take phishers to copy the emails, hook up databases of Twitter handles and email addresses and start pumping out fake “best of Twitter” emails? How long do you suppose it will be before advertisers want “Promoted Stories” sent out to this mailing list? And if you’re using GMail to read these emails, well, Google is making advertising dollars on Twitter’s back! What’s up with that?

I haven’t seen many complaints about this so far in the tech blogs. I think the focus is on Facebook’s IPO and Yahoo’s attempting to fire its way to growth. But I think it’s a bad idea, and I’ve unsubscribed.

If I were working at Twitter, I’d go the exact opposite way. Instead of building a “weekly news magazine”, I’d build a breaking real-time world news ticker. Give me a page with a map of the world. Capture an average of tweet rates by geotag, time of day and day of the week in a database. When the tweet rate takes a sharp increase at a location, light it up on the map and give me a link to search for the tweets.

The Future Of Journalism – Geofeedia or Overview?

 #Blog2012, Books, Computational Journalism, Geospatial Analysis / Mapping, Java, Knowledge Discovery, Real-Time Journalism, Ruby, Twitter Streaming API  1 Response »
May 142012
 

If you’ve been following my tweet stream, you saw me tweet this:

At $1450 a month for five seats, I think the service is overpriced. Moreover, Twitter, Facebook/Instagram, Google/YouTube or Yahoo/Flickr could easily build this into their web sites and deliver it for free, essentially by-passing two middlemen – Geofeedia and the news organization subscribing to Geofeedia. And a clever RSS / Yahoo! Pipes hacker could build something like this for use in a newsroom. For that matter, if you limit yourself to Twitter you can do most of this with Twitter / Advanced Search.

I must admit that I love the idea and think this could evolve into something game-changing. I wrote about the potential for this back in January 2010!

The Twitter Streaming API — How It Works and Why It’s A Big Deal

To get an idea what this could become, check out Knowledge Discovery from Data Streams by Joao Gama.

Moving on, I don’t know how I’ve managed to be a tech blogger writing about computational journalism without discovering Overview until last week, but it happened. Twitter serendipity at work – I was watching my Interactions page and saw a tweet of mine retweeted by @overviewproject. The Overview project is led by Jonathan Stray. You can see the entire team here.

Overview is open source, lives on Github and appears to be a mix of Ruby and Java. I’m currently testing it out for potential inclusion in one of my computational journalism appliances. It’s a browser / desktop application, so most likely it will end up in the successor to Data Journalism Developer Studio  2012LX. If you want to work with it yourself, the instructions are here.

So which of the two represents the future of journalism? Both, of course! With the proper underlying database and real-time knowledge discovery algorithms, Geofeedia could be a game-changer. But in the long run, as a for-profit service, I think they’ll either get acquired or duplicated by the big players..The Overview project, on the other hand, is an open source project. It’s well-funded by the Knight Foundation and Associated Press, and the team is led by one of the well-known names in computational journalism. Overview is certainly going to be part of my future.

 

Computational Journalism Reading List

 #Blog2012, Books, Computational Journalism, Data Journalism, Data Science, Real-Time Journalism  2 Responses »
May 032012
 

A few weeks ago, I volunteered for a Wikipedia editing hack session. In the course of the session, I browsed by the page on Computational Journalism. It’s quite sparse, and as a result, I decided to collect my thoughts on exactly what computational journalism is. I’m still collecting – for me, any discipline is defined by the practitioners, what they do and the tools they use. But I’ve collected a few articles and books that I think are a good place to start.

I’d recommend starting with this article: Computational Journalism: How computer scientists can empower journalists, democracy’s watchdogs, in the production of news in the public interest.

Key Insights

  • The public-interest journalism on which democracy depends is under enormous financial and technological pressure.
  • Computer scientists help journalists cope with these pressures by developing new interfaces, indexing algorithms, and data-extraction techniques.
  • For public-interest journalism to thrive, computer scientists and journalists must work together, with each learning elements of the other’s trade.

Although it’s quite brief, this article defines well the frontiers of computational journalism. In particular, the authors call out five “areas of opportunity”:

  1. Combining information from varied digital sources.
  2. Information extraction.
  3. Document exploration and redundancy.
  4. Audio and video indexing.
  5. Extracting data from forms and reports.

With that article as a basis, I’d recommend the recently-published Data Journalism Handbook. While I consider data journalism a proper subset of computational journalism, the concepts are better known, so it’s a good place to start the journey. It’s also quite comprehensive and down-to-earth. And it’s free.

Participatory Journalism is a collection of essays covering the emerging trends of social media, user-generated content and the new ways journalists interact with their audiences. It’s based mostly on interviews with journalists in major newspapers around the world. I found it rather wordy and overly long, but there really isn’t any other book I’ve found that describes these trends from the point of view of people actually working in newsrooms. And their challenges feed right back into the areas of opportunity called out in the ACM article.

Finally, for those of you looking for a foundation course in journalism, I highly recommend Andy Bull’s Multimedia Journalism. Once you buy the textbook, you get access to the entire web site. It’s been many years since I took a journalism course, and I found that reading the textbook was vital for me as a developer to understand what journalists need from the tools and the technologies.