rocketboytom

Thomas Hillman's research notes and ideas. Examining the relationship between the design-and-use of technology and learning

[rocketboytom]

Computational content analysis for selecting threads

Working with a massive online forum presents a problem for the ethnographer. As I have written about before, having hundreds of thousands of posts in a community all of which can been seen as interactions requires some sort of computational selection criteria.

The criteria I have developed revolves around the notion of thread intensity. I want to know which are the most active threads in terms of number of posts and time between posts, but also in terms of contributors. To slice the data in these ways I have created a spreadsheet with all the posts for a particular subforum threaded into discussions. I first count the number of posts per thread using COUNTIF statements, then calculate the delta between posting times for each post and then the average delta for each thread. I know which usernames correspond to moderators, scientific staff, and amateur participants, so I categorise each post by type of poster and count the number of unique contributors.

So far, this approach has worked relatively nicely. I does not replace looking for specific keywords through KWIC searches, doing concordance analysis to look for themes or SNA, but it does show me the threads that the community has assembled around. By setting different criteria I can go from say 2500 threads to 30 with a selection criteria that I can account for and most importantly argue for. 30 threads is then a manageable number to perform manual content analysis on and decide which should be analysed in detail at the interactional level.

[rocketboytom]

Scraping Facebook groups for interaction analysis

In my previous social media interaction analysis projects I've done a lot of screen scraping - creating a tool that loads each page of a site and copies the data to a spreadsheet file. For our project on the grassroots professional development community that has formed around the flipped classroom movement, we are working with a Facebook group. This means that general approach I have taken with other forums doesn't work at all. Instead, I've been forced to access the data I need through Facebooks Graph API and this has forced me to get more serious about programming in Python.

Fortunately, a number of excellent libraries have been written to access the Graph API through Python scripts. After much experimentation I chose to use jgorset's excellent facepy library. Using facepy as a base and an OAuth key I created through Facebook's own Graph API Explorer, I then built on Simon Mikkelsen's facebook-downloader repository to grab the actual data from the group. Simon has included a nice script for taking the JSON output from Graph API and creating a structured HTML file which can be formated with CSS. By making some alterations, I was able to produce a file that can relatively easily be read with discussion threads that feeds nicely into NVIVO (and probably other CAQDAS packages).

[rocketboytom]

Scraping talk.galaxyzoo.org

In the middle of 2014 Zooniverse froze galaxyzooforum.org and started a new forum at talk.galaxyzoo.org. This new forum has an entirely new structure and is custom built to provide features specific to Zooniverse's citizen science platform such as allowing users to share collections of galaxy images that they have classified. From a technical perspective it is much more complicated than the old forum and involves a lot of AJAX. This means that I have had to create an entirely new scraping tool and since the forum structure is not expressed though static URLs, the tool must interact with the dynamic AJAX elements of the site.

Webscraper.io provides the ability to interact with dynamic elements such as rollovers and javascript buttons, but the tricky part is getting the timing right. On talk.galaxyzoo.org, subforms have unique URLs, but all pagination in the list of threads and pagination within threads themselves is achieved through javascript elements that depending on the complexity of the images posted etc take different amounts of time to load. The site is designed so that pages do not refresh until all the content is loaded and this means that if the timing of the scraper is wrong it will collect the previous page's information despite having trigged a new page to load. This is combined with the added complexity that users can choose to display a collection of galaxy images beside their post which drastically increases the number of images to be loaded. While it would be possible to set a very long pause before the scraper collects information after triggering a page change, that isn't a very efficient way to work with a large number of threads and posts. In the end, the sweet spot for this site on my connection seems to be a delay of about 2000ms.

The JSON script for the scraper looks like this:

{"startUrl":"http://talk.galaxyzoo.org/#/boards","selectors":[{"parentSelectors":["board_page","board"],"type":"SelectorLink","multiple":true,"id":"thread","selector":"div.discussion-summaries div.list div.title a","delay":""}, {"parentSelectors":["thread","thread_page"],"type":"SelectorElement","multiple":true,"id":"post","selector":"li div.post","delay":""}, {"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"user","selector":"a.user:nth-of-type(2)","regex":"","delay":""}, {"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"content","selector":"div.content","regex":"","delay":""}, {"parentSelectors":["post"],"type":"SelectorGroup","id":"links","selector":"p a","delay":"","extractAttribute":"href"}, {"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"date","selector":"span.on-hover","regex":"","delay":""}, {"parentSelectors":["thread"],"type":"SelectorElementClick","multiple":true,"id":"thread_page","selector":"div.discussion-topic div.pages","clickElementSelector":"div.discussion-topic a.page-link","clickElementUniquenessType":"uniqueText","clickType":"clickMore","discardInitialElements":false,"delay":"4000"}, {"parentSelectors":["board"],"type":"SelectorElementClick","multiple":true,"id":"board_page","selector":"div.discussion-summaries div.pages","clickElementSelector":"div.discussion-summaries a.page-link","clickElementUniquenessType":"uniqueText","clickType":"clickMore","discardInitialElements":false,"delay":"2000"}, {"parentSelectors":["thread"],"type":"SelectorElement","multiple":false,"id":"collection","selector":"div.stack.discussions div.one-third","delay":""}, {"parentSelectors":["collection"],"type":"SelectorLink","multiple":false,"id":"collection_title","selector":"h3 > a","delay":""}, {"parentSelectors":["collection"],"type":"SelectorText","multiple":false,"id":"collection_user","selector":"a.user","regex":"","delay":""}, {"parentSelectors":["_root"],"type":"SelectorLink","multiple":true,"id":"board","selector":"div.board-summary div.title a","delay":""}],"_id":"talk_galaxyzoo_org"}

[rocketboytom]

Re-threading the once threaded

One of the problems with scraping is that the order the scraper moves through a forum site may not follow the logical reading order for posts. This means that while I managed to collect all 65,000 posts into a series of spreadsheet files for each sub-forum, the order the posts appeared made threads totally unreadable. If I only wanted to perform descriptive statistical analysis on the posts this wouldn't be a problem, but I want to analyse the discussions as interactions and so clearly they needed resorting. I tried to import the CSV files into qualitative data analysis program MaxQDA and use it to sort out the posts, but quickly realised that what I needed was to see each thread as separate document organised by sub-forum in the QDA database and not each post organised by thread. This meant that I needed to reconstitute the threads within the spreadsheet files and split each thread off as separate workbook files before importing them into MaxQDA. Fortunately, after a great deal of trying I managed to get Excel to perform the task:

I performed a custom sort on each spreadsheet. Level 1 of the sort was the thread title (this groups all the posts for a thread), and level 2 was the timestamp (this sorted the posts within each thread).

I then used pivot tables to filter the data by thread and make each thread its own sheet.

Then I used this VBA script to automatically save each sheet as a new workbook (VBA scripts only work easily on Windows versions of Excel so I was forced to fire-up the old virtual machine on my Mac to make this work).

And voila! I imported the spreadsheets for each thread into MaxQDA and ended up with a threaded database of posts to search through and code.

[rocketboytom]

Scraping galaxyzooforum.org

Between 2007 and 2014 Galaxy Zoo participants maintained a forum at galaxyzooforum.org that was very active for at least the first 3 or 4 years. It amassed over 65,000 posts in nearly 20,000 threads and had just over 9,000 members.

To scrape the posts from galaxyzoo.org I used Martin Sbalodis’ webscraper.io Chrome extension to write my own tool. Since galaxyzooforum.org is based on Simple Machines’ relatively uncommon SMF2 forum platform, there were no pre made scrapers or hacks to poll the forum backend for information as there is for platforms like phpBB. Since SMF2 as implemented on galaxyzooforum.org has no dynamic elements it was relatively straightforward to create a tool that loads each page in succession and collects the posts.

The tool I created breaks down each post into the poster, time posted, text, URLs and image URLs. In addition, the post order within each thread is collected to make reassembling the threads after scraping easier.

The JSON script for the scraper looks like this:

{"startUrl":"http://www.galaxyzooforum.org/index.php?board=18.0","selectors":[{"parentSelectors":["_root","pagination_forum"],"type":"SelectorLink","multiple":true,"id":"pagination_forum","selector":"div.pagelinks.floatleft a.navPages","delay":""},{"parentSelectors":["_root","pagination_forum"],"type":"SelectorLink","multiple":true,"id":"thread","selector":"td.subject span a","delay":""},{"parentSelectors":["thread","pagination_thread"],"type":"SelectorElement","multiple":true,"id":"post","selector":"div.post_wrapper","delay":""},{"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"user","selector":"h4 a","regex":"","delay":""},{"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"time","selector":"div.keyinfo div.smalltext","regex":"","delay":""},{"parentSelectors":["post"],"type":"SelectorText","multiple":false,"id":"text","selector":"div.inner","regex":"","delay":""},{"parentSelectors":["thread","pagination_thread"],"type":"SelectorLink","multiple":true,"id":"pagination_thread","selector":"a.navPages","delay":""},{"parentSelectors":["post"],"type":"SelectorGroup","id":"links","selector":"div.inner > a.bbc_link","delay":"","extractAttribute":"href"},{"parentSelectors":["post"],"type":"SelectorGroup","id":"images","selector":"div.inner > img.bbc_img","delay":"","extractAttribute":"src"}],"_id":"galaxyzoo"}

Essentially, the scrape loads each thread of a subforum and then recursively each page of posts within a thread. It uses specific CSS elements of the forum structure to identify specific information and produce a CSV file that contains all the data.

Since there is 65,000 posts on galaxyzooforum.org, I decided to scrape each subforum independently to limit the damage if the scraper broke. This procedure worked well and I was able to scrape each subforum to a separate CSV file. I then took this CSV file and used TextWrangler’s brilliant ‘Zap Gremlins’ function to clean up some strange artefacts that appeared because of changes in text encoding. 

[rocketboytom]

Drowning in forum posts

My training as a social scientist has focused on ethnographic methods and the use of detailed video ethnography has been the cornerstone of my research practice. But, like many social scientists in the last few years, my attention has turned more and more to online interactions between people and this has posed significant challenges. As many have lamented, the sheer volume of data that must be managed is in many ways incompatible with the detailed, situated approaches I am trained in. Finding ways to sort through enormous flows of interactions and make rigorous choices about which interactions to focus my detailed analysis on has proven to be both fascinating and frustrating. A case in point is my current work to understand informal learning in communities of amateur 'citizen scientists' who contribute to large science projects through their efforts online. One of the communities I am studying has had an active discussion forum for the past eight years and finding a way to manage 65,000 posts, many of which form detailed scientific discussions that take place over several months, has forced me to find new ways of working.

[rocketboytom]

Quick & dirty social media scrapping

In my work to examine social media use, particularly social photography, I have been faced with the challenge of collecting and managing data from social networks. Very often, accessing a social network through its official web, desktop or mobile apps fails to provide the features necessary for research. This is somewhat obvious since social networks are designed to support use not research of their use. In addition, many social networks, such as Twitter, limit the availability of data through searches to fairly recent time frames. After exploring a number of different approaches for using official and third party interfaces to networks such as Flickr and Instagram, I realized that the best way for me to move forward was to capture as much of the data I wanted as I could from a network and then be free to experiment with different ways of managing and presenting it. Using combinations of adaptations of existing social media scraping tools and my own simple inventions, I have created several home-brew ways of collecting and managing data from social networks.

Basic approach

My goal with scraping social media is to extract as much relevant data as possible to a format that restricts later processing and analysis as little as possible. To that end, I decided that a simple spreadsheet was probably the best way to store data. Since many social networks restrict the window of data that is accessible, I also decided that a solution which automatically updated without my needing to trigger a process would be best. Based on these criteria, it became evident that a so-called cloud based process would meet my needs. I decided to use the spreadsheet app that is part of Google Drive since it exists in the cloud and effectively runs all the time. For social media scraping, Google spreadsheets has the major advantage that it will populate a spreadsheet based on a feed in such common formats as XML, RSS and JSON, and a script can be written that will cause the feed to be checked automatically at an interval defined by the user. With this key solution that allows data to be constantly fed into a spreadsheet where it can be filtered, organized and stored, the next challenge is to get a specific social network to provide data in the form of a usable stream.

Automatically generated spreadsheet of Flickr images tagged with 'göteborg naturhistoriska'

Twitter

Of all the networks I have tried to scrape, Twitter is the one with the most tools available that might be of use to researchers. Several sites such as http://snapbird.org/ archive tweets, allowing searches that go back far longer than Twitter's own 5 day window. I tried these sites but found them cumbersome to use and limited. Instead, I have been using Martin Hawksey's Twitter Archiving Google Spreadsheet (TAGS). This set of extensions and scripts for Google Spreadsheet conducts periodic searches of Twitter, archives the results and provides a variety of visualization methods. Using Twitter's advanced search operators, it is possible to create a self updating archive for quite complex searches e.g tweet's mentioning 'obama', from within a 5 km radius of Washington DC that contain hyperlinks: https://twitter.com/search/realtime?q=obama+near%3A+washington+within%3A5km+filter%3Alinks&src=typd

Archived tweets mentioning 'universeum' visualized through Martin Hawksey's TAGS Google Spreadsheet extensions

Instagram

For Twitter I was able to find a relatively complete solution for my needs. Instagram, on the other hand, is much newer and required me to combine a variety of web-based service to build a functional solution. 

To scrape instagrams based on my own search criteria and automatically archive them I use the following process:

Create an IFTTT (If This Then That) recipe that searches Instagram for particular keywords at a particular interval, then adds the results as new lines in a Google Spreadsheet. Here is an example recipe that searches Instagram for 'universeum' and filters the information provided into columns in a Google Spreadsheet.

To scrape instagrams taken at a specific location, I use this process:

Define a geographic search using spots.io. This tool allows you to specify a location such as a park or museum within a particular city and receive all the instagrams geotagged with the corresponding coordinates.

Spots.io provides RSS feeds for searches. This means that it is possible to take the RSS feed for a geo-search and feed it into an IFTTT recipe in the same way as a straight Instagram search. Simply create a recipe that is triggered every time an Instagram is added to the spots.io RSS feed that writes the results to a Google Spreadsheet.

Results for Instagrams geotagged at Gothenburg Natural History Museum

Flickr

To extract information from Flickr I use a similar process to the one I use with Instagram:

Define a search with Steven DeGraeve's Flickr RSS Feed Generator.

Use the resulting RSS feed to create an IFTTT recipe that filters the data and creates useful columns in a Google Spreadsheet.

Steven DeGraeve's Flickr RSS Generator

Other social media

The basic process I outline here is a simple one. It takes advantage of the cloud based nature of Google Spreadsheets to automatically assemble data from social networks. In principle, any information that can be rendered as XML, RSS or JSON can be fed into a spreadsheet. The trick is finding or creating a tool that can produce such a feed. In many cases, feeds can be found that have been created for completely different purposes e.g. DeGraeves Flickr feed generator which was created to make it possible for users to make live updating slideshows from Flickr images. Beyond regular google searches for ways to turn social media into a usable feed, scraping specific resources can be found at https://scraperwiki.com/ and https://wiki.digitalmethods.net/Dmi/ToolDatabase.

[rocketboytom]

Geocaching in kindergarten

Here is a really detailed site developed by Gothenburg kindergarten teacher Ann-Charlotte Keiller who is geocaching with her students. Its fantastic to see 4-6 year olds working together using GPS and solving clues to find caches.

Link in Swedish - English available through Google Translate button at bottom right corner of screen.

[rocketboytom]

Automatically synchronized audio and notes

Here's an idea for interviews. AudioNote is an iOS app designed for people who want to take notes during lectures. It records audio and has a note pad. Everytime you make an entry on the note pad, it tags the place in the audio recording that the entry was made. The result is written notes that are synchronized with the audio. Used during interviews instead, AudioNote offers a useful way to make notes without needing to manually record times or try to describe the point in the interview. Managing an interview is already a difficult task and trying to take notes makes it even harder. Anything that can make the process easier is probably worth a try.

[rocketboytom]

[rocketboytom]

iOS video-screen-capture part 2

Apple seems to have a problem with people capturing screen-video directly from an iOS device so they are not approving apps that allow it. This is a pain for anyone doing research that could benefit from screen-videos (like me).

Looking for a work around, I came across Matt Galligan's really well put together instructions for using AirPlay to share an iOS device screen to a Mac. By setting a Mac up as an AirPlay receiver, it is possible to share an iOS screen and then do the capturing on the Mac side. It turns out to be a fairly robust way to do recording and has the added benefit of being wireless (within a given WIFI network).

[rocketboytom]

iOS video-screen-capture

UPDATE: Apple has decided they don't like this kind of thing and have removed Display Recorder and similar apps from the App Store. Looks like Jailbreaking is the only option again.

I recently came across this new app, Display Recorder, that can record video of the screen and sounds from any iOS device (iPhone, iPad, iPod Touch). This has some great research potential and though it has been possible to do this with jailbroken devices for a while, the new feature is that it allows researchers to record the screens of participants own devices not only those provided as part of a study.

There are some issues noted by reviewers that might cause researchers trouble such as the app not recording the viewing window when users take videos or photographs with the cameras on their devices, but many of these appear to have workarounds described on the developer's how-to page.

Here's hoping that the developer, Bugunsoft, adds the ability to simultaneously record the screen and back-facing camera on iPhones and iPads. Screen action and the user in a single split-screen video, that would be a dream mobile-tech research app!

[rocketboytom]

Password protecting videos for distribution to participants

Until relatively recently Digital Rights Management (DRM) was a bit of a dirty term for me. If I had any interaction with a media file that had been locked with DRM so that it could only be used for a set period or on a specific computer, it was a frustrating experiences. I never imagined that I would end up trying to add DRM to videos myself.

A few weeks ago, a research project I am working on was faced with an ethical dilema. We had filmed in several classrooms and needed to send the videos to the teachers so that they could review them before attending focus groups where they would discuss their practices. The problem was that we could not get ethical approval to distribute the videos online or via DVDs because of the risk that they would fall into the wrong hands. What we needed was video files that could only be seen with a password and could not be copied. The solution was a relatively simple form of DRM.

The solution I found was to use a program called GreenForce Player to create self-contained video players for each file. GreenForce is not a particularly nice video player but it has one very unusual feature. It allows you to lock a video with a password, prevent it from being copied, have it become un-readable after a specific date, and even make it so that it will only play on one specific computer. Unlike most very complicated commercial DRM systems, GreenForce is free and relatively simple to use. The only major downside I could find is that it is Windows only (all our teachers are Windows users but our research team are mostly Mac users) .

For our particular application, we distributed a DVD to each teacher with their video clips packaged as GreenForce self-contained players. We gave all the videos for a single teacher the same password and set the files to become unreadable a few days after the focus-group sessions. To be sure that the teachers could all play the videos regardless of what software they had on their PCs, we also distributed the K-Lite Codec Basic Pack on the DVDs and asked them all to install it. Following this procedure we had no problems with teachers not being able to play the files.

[rocketboytom]

Translating a 'counting box' to a touch screen...

[rocketboytom]

One of the earliest known examples of math homework

Incredible - plus ça change!

[rocketboytom]

"Join OpenClass today and help us bring down the walls in education"

Wait... Aren't textbook publishers the creators of one of the biggest walls to open accessible education for all? Don't textbooks cost a fortune? Isn't textbook publishing a multi-billion dollar industry based on making education exclusive to those who can afford their books? Isn't Pearson the world's largest textbook publisher?

Now I'm confused.

[rocketboytom]

Norwegian online math learning environment Kikora. This video (in Norwegian) is interesting too.