We had a hugely productive meeting of the research team today. We write here its documentation.
Goals
Spot The Future research activities are about re-using the online conversation on the Edgeryders platform research data. The interface between conversation and research is technological. The Edgeryders website runs on a technological stack, and we need to think on how to enrich that stack so that:
- research can be conducted easily and cheaply
- without being in the way of conversation
- while being transparent about our research activities and methodology
- with an eye on long-term stewardship both of primary (posts, comments) and secondary (ethnographic coding) data.
We came up with the following solution:
Ethnographic research
Coding on Edgeryders
Ethnographic coding happens on the platform itself. “Coding” in the ethnography context means assigning a keyword to a selection of text, typically a sentence or paragraph. For example, suppose you want to assign the tag “cookies” to the sentence “This is a sentence.”. Coding on Edgeryders would result in assigning RDFa attributes to the sentence, like this:
<span property=“eoe:topic” resource=“[eoe:cookies]”>This is a sentence.</span>
This tagging system can be used by everyone with the “content manager” role, but is for now just meant for being used by @Inga Popovaite of course. Usage goes like this:
- Creating a new tag.
- Go to the CKEeditor styles list and click the "Clone" operation for a style whose name starts with "eoe_". (That means "Edgeryders Online Ethnography" and is a namespace we invented to mark these tags.)
- In the style form, adapt the "Administrative Title" field to be different from the original you cloned. For consistency, usually keep it the same as the "Title" field more below.
- Click "Edit" behind the "Machine name" field in the top of the form, and adapt it to start with "eoe_" followed by a short version of the Administrative title field, using only lowercase letters, digits and "_".
- Adapt the "Title", "Property" and "Resource" fields according to their field help texts.
- Click "Save".
- If needed, you can click "Edit" again to adapt all fields of your tag, except the "machine name" one. To adapt this, you have to clone your style rule and afterwards delete the original. Also note that these changes only affect new tagging activity. Old taggings use the old values.
- Tagging some text.
- Click "Edit" for the piece of content you want to tag, or to proceed tagging (usually posts and comments).
- Select "Text Format: Filtered HTML + Tagging" below the editor.
- Select a piece of text that you want to tag.
- Click the "Styles" dropdown in the left of the editor toolbar and there, click the tag you want to use.
- When mousing over a tag for a second in the "Styles" dropdown, a tooltip with the full name will appear. This helps with long names that are not visible completely. The same tooltip also appears when mousing over tagged text in your editor. This lets you know which tag you used there, as only types of tags (like "topic", "place" etc.) will be optically distinguishable. (Means, optical rendering of tags will not regard for differences in the "resource" attribute.)
- Repeat as above, and when you're done select "Text Format: Filtered HTML" again and click "Save". Switching the text format back is important, because else the original authors (who can't use the tagging text format) would be disallowed from editing their own content. The tagging itself is kept of course, the difference is just that the editor will miss the list of tagging styles, and tags are not rendered visually.
- If you forgot to reset the text format before saving, you can of course edit the content again and fix this issue. It is also ok to keep the text format at "Filtered HTML + Tagging" as long as you are in your editing session (that is, using the "Save and Edit" button for saving your work every now and then).
- Removing tags from text.
- In the tagging editor, mark text from which you want to remove all tags.
- Click the "Remove Format" button in the toolbar (looks like
Tx
). This will remove all formats from the text, both all tags and visual formatting. - Re-apply tags you want to keep. This is relevant in cases where multiple tags had been applied at once.
- Re-apply visual formatting.
- Power user mode. If anything goes really wrong with tagging, it can be fixed up again in the HTML source mode. For that click the "Switch to plain text editor" link below the tagging editor, and when done click "Switch to rich text editor". This mode is also great for removing tags while keeping other tags and visual formatting that is applied to the same text.
Keep in mind that, for transparency reasons, users are allowed to see the tagging of their own content by navigating to their own posts and comments, clicking on “Edit” and then selecting “Switch to plain text editor”. They can also see individual tags when “accidentally” mousing over tagged text, which will make a tooltip to appear, showing the tag’s name.
TODO. The following functionality is not yet implemented, but will be added soon:
- A way to mark what nodes (including their comments) have been tagged already.
Analysis with a CAQDAS tool
@Matthias will write a script that exports STF content in a format that can be imported with an open source CAQDAS tool. Like WEFT-QDA, but there are better alternatives (so far CATMA seems best, and it’s also web-based). Inga can then explore the data using that tool.
Network analysis
Most of the network analysis will use tools external to Edgeryders. The interface is the Drupal module Views-Datasource (already installed and enabled). This module allows to create queries to the Edgeryders database and export them in JSON format. @Alberto and @brenoust will work together to create the queries relevant here. Benjamin will then write the scripts that transform the JSONs into networks.
We wish to explore the relationships between social interaction (as represented by a network of comments) and semantics (as represented by ethnographic coding and perhaps output from natural language processing algorithms) in the STF conversation. To do this, Benjamin will write scripts to retrieve the tags from the full text of posts and comments.