OUseful.Info, the blog…

Trying to find useful things to do with emerging technologies in open education

Posts Tagged ‘tw

Fishing for OU Twitter Folk…

with one comment

Just a quick observation inspired by the online “focus group” on Twitter yesterday around the #twitterou hashtag (a discussion for OU folk about Twitter usage): a few minutes in to the discussion, I grabbed a list of the folk who had used the tag so far (about 10 or people at the time), pulled down a list of the people they followed to construct a graph of hashtaggers->friends, and then filtered the resulting graph to show folk with node degree of 5 or more.

twitterOU - folk followed by 5 or more folk using twitterou before 2.10 or so today

Because a large number of OU Twitter folk follow each other, the graph is quite dense, which means that if we take a sample of known OU users and look for people that a majority of that sample follow, we stand a reasonable chance of identifying other OU folk…

Doing a bit of List Intelligence (looking up the lists that a significant number of hashtag users were on, I identified several OU folk Twitter lists, most notably @liamgh/planetou and @guyweb/openuniversity.

Just for completeness, it’s also worth pointing out that simple community analysis of followers of a known OU person might also turn up OU clusters, e.g. as described in Digging Deeper into the Structure of My Twitter Friends Network: Librarian Spotting. I suspect if we did clique analysis on the followers, this might also identify ‘core’ members of organisational communities that could be used to seed a snowball discovery mechanism for more members of that organisation.

PS hmmm… maybe I need to do a post or two on how we might go about discovering enterprise/organisation networks/communities on Twitter…?

Written by Tony Hirst

October 14, 2011 at 1:01 pm

Posted in Anything you want

Tagged with , , ,

Segmented Communications on Twitter via @-partner Messaging

with 5 comments

As this blog rarely attracts comments, it can be quite hard for me to know who, if anyone, regularly reads it (likely known suspects and the Googlebot aside). The anonymous nature of feed reader subscriptions also means it tricky to know who (if anyone) is reading the blog at all…

Twitter is slightly different in this regard, because for the majority of accounts, the friends and followers lists are public; which means it’s possible to “position” a particular account in terms of the interests of the folk it follows and who follow it.

Whilst I was putting together A Couple More Social Media Positioning Maps for UK HE Twitter Accounts, I considered including a brief comment on how the audience of a popular account will probably segment into different interest groups, and whether or not there was any mileage in trying to customise messages to particular segments without alienating the other parts of the audience.

Seeing @eingang’s use yesterday of a new (to me) Twitter convention of sending hashtagged messages to @hidetag, so that folk following the hashtag would see the tweet, but Michelle’s followers wouldn’t necessarily see the tagged tweets (no-one should follow @hidetag, NO_ONE ;-), it struck me that we might be able to use a related technique to send messages that are only visible to a particular segment of the followers of a Twitter account…

How so?

Firstly, you need to know that public Twitter messages sent to a particular person by starting the message with an @name are only generally visible in the stream of folk who follow both the sender and @name; (identifying this population was one of the reasons I put together the Who Can See Whose Conversations In-stream on Twitter? tool).

Secondly, you need to do a bit of social network analysis. (In what follows, I assume a directed graph where a node from A to B means that A follows B, or equivalently, B is a friend of A.) A quick and dirty approach might be to use in-degree and out-degree, or maybe the HITS algorithm/authority and hub values, as follows: identify the audience segment you want to target by looking for clusters in how your followers follow each other, then do a bit of network analysis on that segment to look for Authority nodes or nodes that are followed by a large number of people in that segment who also follow you. If you now send a message to that Authority/high in-degree node, it will be seen in-stream by that user, as well as those of your followers who also follow that Authority account.

This approach can be seen as a version of co-branding/brand partnership: conversational co-branding/conversational brand partnerships. Here’s how it may work: brand X has an audience that segments into groups A, B and C. Suppose that company Y is an authority in segment B. If X and Y form a conversational brand partnership, X can send messages ostensibly to Y that also reach segment B. For a mutually beneficial relationship, X would also have to be an authority in one of Y’s audience segments (for example, segment P out of segments P, Q, and R.) Ideally, P and B would largely overlap, meaning they can have a “sensible” conversation and it will hit both their targeted audiences…

For monitoring discussions within a particular segment, it strikes me that if we monitor the messages seen by an individual with a large Hub value/out-degree (that is, folk who follow large numbers of (influential) folk within the segment). By tapping into the Hub’s stream, we get some sort of sampling of the conversations taking place within the segment.

These ideas are completely untested (by me) of course… But they’re something I may well start to tinker with if an appropriate opportunity arises…

Written by Tony Hirst

October 13, 2011 at 10:34 am

Posted in Infoskills

Tagged with ,

Using Twitter Lists to Define Custom Search Engines

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A long time ago, I used to play with search engines all the time, particularly in the context of bounded search, (that is, search over a particular set of web pages of web domains, e.g. Search Hubs and Custom Search at ILI2007). Although I’m not at IWMW this year, I can’t not have an IWMW related tinker, so here’s a quick play around IWMW related twittering folk…

To start with, let’s have a look at the IWMW Twitter account:

IWMW lists

We see there are several twitter lists associated with the account, including one for participants…

Looking around the IWMW10 website, I also spy a community area, with a Google Custom search engine that searches over institutional web management blogs that @briankelly, I presume, knows about:

Institutional Web Managemet blogs search engine

It seems a bit of a pain to manage though… “Please contact Brian Kelly if you would like your blog to be included in this list of blogs which are indexed”

Ever one to take the lazy approach, I wondered whether we could create a useful search engine around the URLs disclosed on the public Twitter profile page of folk listed on the various IWMW Twitter lists. The answer is “not necessarily”, because the URLs folk have posted on their Twitter profiles seem to point all over the place, but it’s easy enough to demonstrate the raw principle.

So here’s the recipe:

- find a Twitter list with interesting folk on it;
- use the Twitter API to grab the list of members on a list;
- the results include profile information of everyone on the list – including the URL they specified as a home page in their profile;
- grab the URLs and generate an annotations file that can be used to import the URLs into a Google Custom Search Engine;
- note that the annotations file should include a label identifier that specifies which CSE should draw on the annotations:

Google CSE config

Once the file is uploaded, you should have a custom search engine built around the URLs folk followed in the twitter list have revealed in their twitter profiles (here’s my IWMW Participants CSE (list date: 12:00 12/7/10)

Note that to create sensibly searchable URLs, I used the heuristics:

- if page URL is example.com or example.com/, search on example.com/*
- by default, if page is example.com/page.foo, just search on that page.

I used Python (badly!;-) and the tweepy library to generate my test CSE annotations feed:

import tweepy

#these are the keys you would normally use with oAuth
consumer_key=''
consumer_secret=''

#these are the special keys for single user apps from http://dev.twitter.com/apps
#as described in http://dev.twitter.com/pages/oauth_single_token
#select your app, then My Access Token from the sidebar
key=''
secret=''

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(key, secret)
api = tweepy.API(auth)

#this identifier is the identifier of the Google CSE you want to populate
cseLabelFromGoogle=''

listowner='iwmw'
tag='iwmw10participant'

auth = tweepy.BasicAuthHandler(accountName, password)
api = tweepy.API(auth)

f=open(tag+'listhomepages.xml','w')

cse=cseLabelFromGoogle

f.write("<GoogleCustomizations>\n\t<Annotations>\n")

#use the Cursor object so we can iterate through the whole list
for un in tweepy.Cursor(api.list_members,owner=listowner,slug=tag).items():
    if  type(un) is tweepy.models.User:
      l=un.url
      if l:
        l=l.replace("http://","")
        if not l.endswith('/'):
          l=l+"/*"
        else:
          if l[-1]=="/":
            l=l+"*"
        f.write("\t\t<Annotation about=\""+l+"\" score=\"1\">\n")
        f.write("\t\t\t<Label name=\""+cse+"\"/>\n")
        f.write("\t\t</Annotation>\n")

f.write("\t</Annotations>\n</GoogleCustomizations>")

f.close()

(Here’s the code as a gist, with tweaks so it runs with oAUth.)

Running this code generates a file (listhomepages.xm) that contains Google custom search annotations for a particular Google CSE, based around the URLs declared in the public twitter profiles of people listed in a particular list. This file can then be uploaded to the Google CSE environment and used to help configure a bounded search engine.

So what does this mean? It means that if you have a identified a set of people sharing a particular set of interests using a Twitter list, it’s easy enough to generate a custom search engine around the webpages or domains they have declared in their Twitter profile.

Written by Tony Hirst

July 12, 2010 at 12:18 pm

Posted in Tinkering

Tagged with , ,

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