Tweetping and the Semantic Web

Recently, recurring birthday girl Devon tweeted about  Tweetping, a website tracking world-wide tweet counts. Tweetping may be the first step to realizing a Semantic Web. The term, developed in the 1960s, describes a web network that enables machine-read metadata to recognize relationships between webpages and web searches and attempts to establish these links in order for users more accurately and conveniently access the web.

I’ve had tweetping open for maybe ten minutes now and I’ve watched the number of tweets rise exponentially. What the site does-recording tweets by characters used, by hashtag (by another word, folksonomies-organically developed content retrieval tags instigated by small groups or individuals , words, mentions, place of origin, is the beginning of the Semantic Web. These ontologies -a set of data within a domain (of discourse)-touch at the possibilities of a Semantic Web.

The computer/algorithm is tracking data, but to be part of the Semantic Web, data needs to be relatable. Tweetping may track hashtags and @mentions, but offers no way of viewing the amount of times any given hashtag was used, or who/where/when the hashtag was used. In Semantic Web terms, this is provenance. Provenance is an important aspect of the Semantic Web because it can show what information is available to different areas of the globe, the density of information/technology availability (Africa has noticeably fewer tweets than other inhabited areas), and how inhabitants in the area feel about the information.  Archiving is an important function in the Semantic Web, as it is through archiving that metadata relationships can be recognized.

Moving towards a Semantic Web changes conceptions of websites and what counts as data. Twitter is an ideal example, as the social media platform is often derided for user’s tweets being thin-largely irrelevant posts (i.e. “oh snap”). But authors Tim Berners-Lee, Nigel Shadbolt and Wendy hall would argue that twitter is a a great example for Semantic Web development-given the websites tendency towards shared conceptionualization and peer-to-peer protocols. Twitter has changed how information is recorded, communicated, and archived. Twitter users have the ability to list information via topic, or group information in any way they want to. These lists can also be shared, altered, etc.

While tweetping is an imperfect example of the Semantic Web, it is a step in the right direction. However, it can easily be adapted. It would not take much to expand Tweetping to track tweet posts by topic, area, etc. As stands, it is an interesting look at how machine-and not humans-track data. It also stands as an interesting contribution to web science, a science that seeks to develop an understanding of how information systems (both human and machine) operate on a global scale.

Tweetping offers an interesting look a global data trends-though again, only through seeing repeated hashtags in this version. As users of the Semantic Web, we must be aware that we are not just tweeting, not just blogging, not just idly surfing the web. We are contributing to the global information database.

Categories: #IAMondays, information architecture, mapping, semantic web, twitter | Tags: | 2 Comments

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2 thoughts on “Tweetping and the Semantic Web

  1. I think Tweetping is really cool, but I would argue it’s not the only one in the step towards a Semantic web; there are plenty of other sites alike that offer similar information. I think it’s important to look at the how and why of Tweetping too. Why was it created? To help people connect? Or to study the relationships among numbers? I would disagree that Twitter is just thin tweets. Surely, there are plenty of people who thin tweet, but I’d say that there are plenty more who thick tweet. Anyways, I’m wondering what Tweetping’s goal really is. To look at similar tweets? Or to see why people tweet similarly? Or to just study the numbers?

  2. Another factor that I think is missing here is the fact that most people I know use Twitter more as a communication program, sort of like a giant chat room where you choose who you see. Looking at Twitter in this way is very different from considering it an information database. Sure, you could study how many tweets are made, where they come from, and whether the content is thin or thick, but that’s hardly considering everything Twitter is used for.

    Metadata to analyze the connection between web pages and searches is fine, but what about the relationships? Nothing I see here seems to tell me anything about how often certain people have conversations, or how long they chat for. I’d find a Twitter information database more interesting if I could see something like, say, an average conversation between a user in the US and one in Canada lasts 17 minutes and comprises 86 tweets.

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