Comments on PJ’s Quill Connect

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I found the algorithmically-generated Quill Connect summary report of my history in the “Twitterverse” to be informative and insightful about the sheer power of algorithms, their relevance and some of the cautions. In terms of the power of algorithms and ‘big data,’ I would never have been able to examine the 6,104 tweets from myself and my recent followers that Quill Connect claims to have examined. In his forthcoming paper “The Relevance of Algorithms,” Tarleton Gillespie suggests that the key logic governing the flows of information generated by algorithms produce the “power to enable and assign meaningfulness” (Langlois 2012). This Quill Connect summary certainly provided me with some ‘food for thought’ to consider about my influence or lack thereof, and how I might interface more effectively with Twitter in the future. The capability of the algorithm to synthesize my personal data also validated Gillespie’s characterization of them to be “manna from heaven” for researchers.

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I was very reticent to join the “Twitterverse” until three years ago in 2012 when I finally realized that something profound was happening with social media, and that I had better
get ‘on-board.’ I ‘lurked’ the Coursera E-Learning MOOC and was so intrigued that I applied to the Edinburgh MScDE Programme. My engagement as a ‘digital learner’ and confidence level with social media continues to grow, but I still remain relatively cautious and conservative about my online presence and exposure because I have genuine concerns about security and privacy.

Gillespie discusses the emergence of the algorithm as “a trusted information tool” and the inherent “fundamental vulnerability” and lack of transparency that are engendered by “a new knowledge logic.” So, while my own Quill Connect report gives me some comfort that I now have a viable online history, presence and that people are interested in what I tweet, there remains a lingering skepticism of putting faith in unseen algorithmic machines that may be susceptible to human error, bias or manipulation.

I tweet ‘right at average’ for my collection of followers at 2 per week. Quill Connect indicates that I have 42 followers, which is fewer than average, landing me in the 42nd percentile of Twitter users measured by followers. This modest following does not bother me at this stage of development because I am not particularly concerned about my ‘influence’ beyond the ‘safe’ environment of my online learning community. I am concerned, however, that I have attracted other followers outside that community that I do not know.

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I have been inspired by this EDC course to be more active online, and as a result, my recent Twitter activity has picked up. This week, I sent out 19 tweets this week, eight more than last week and above my weekly average. It is curious that my most popular tweet was about the issue of time management and MOOCs shared with EDC peer Ben. For me, this tweet was just a routine
information-sharing exchange, but it seems that this theme resonated with some of my followers.

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The most popular tweet from recent followers was very curious indicating my affiliation with Vedic Sage. I believe that I attracted Vedic Sage as a follower because of previous online digital learning coursework that I had done on meditation; for example, online postings of ethnographic observation activities at the Buddhist Centre in Second Life.

It is accurate that my Tweets are most focused on Education, Business, Technology, and Politics. I always try to be positive in tone. While this report indicates that the sentiment of my Tweets “don’t skew positive or negative,” ….it also points out: “your followers skew more positive than you overall.” This commentary may cause me to reflect more in the future about how I craft Tweets, and to be more circumspect about the subtleties of tone and sentiment.

I am not overly concerned with increasing my “Twitter reach.” So I am unlikely, at this juncture anyway, to deliberately try to increase my reach is to repeating myself. However, I may heed the advice to follow people in my areas of interest, and/or people who follow the people that I follow.

6 thoughts on “Comments on PJ’s Quill Connect”

  1. This is a super description of your explorations with QuillConnect PJ, and some great reflection on how a service like this might guide our future social media activity.

    You’ve focussed on the statistical measures here, and I wondered if you could say a little more about what you think the implications of this might be. I know that you’ve stated which kinds of things you are comfortable with, but I’m wondering more about the general premise that we compare ourselves to ‘average use’. What does that really mean for a service like Twitter? How has this organisation decided on those particular averages, and what understandings of social media are driving that? It seems to me that ‘tweeting 2 times a week’ is more about a kind of corporate social media strategy, than considering the educative value of reading and/or posting to Twitter. So the broader question here is, who and what are constructing the ‘normal’ Twitter user, and what might that mean for educational use of the service?

    Your focus on the stats is also interesting, as one of the core offerings of QuillConnect is the data-to-text computation. This is a burgeoning area of algorithmic web development, where articles are ‘written’ automatically from lots of different kinds of web data. (I was at a data-to-text event earlier this week in Edinburgh http://www.macs.hw.ac.uk/InteractionLab/d2t/). Ed shared this Tweet recently which is typical of this data-to-text field, an article ‘written’ from stock market data:

    Other big developments include sports articles written from various sources of data like sports stats and social media comments.

    So, what are the issues around writing text about your Twitter activity? Does that make it more believable? Some of this work is motivated by the idea that stats are simply to ‘dry’, and that people prefer written accounts of activity.

    1. Jeremy, thanks for generous and penetrating feedback. I need to take a look at Ed’s Tweet and explore data-to-text, then I’ll come back in a day or so and blog about it. this might be an interesting final assignment topic.
      Cheers, PJ

  2. Hi PJ, this is interesting. I found my QuillConnect report much less informative than my Discovery timeline analysis, so I didn’t do much with it. However, I have been inspired by your post to go back and reflect on the differences!

    1. Katherine, I suggest taking Quill Connect with a ‘grain of salt.’ While I was enthusiastic last week, I think I feel into proverbial ‘trap’ of ‘instant gratification’ with data-to-text tools. I tweeted extraordinarily this past week for out Twitter Tutorial, over 30 more tweets than usual, but my Quill Connect still reports me averaging at about 2 per week, so I am more skeptical and cynical this week about Quill Connect. I try to take a look at your Discovery timeline. Cheers, PJ

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