Why am I still writing?

I am still writing my thesis. Still. Yes, still. I am still writing my thesis. Oh my goodness, I am still writing my thesis!

When I began my PhD more than three years ago, I was confident that I would be one of those irritating students who submitted their work spot on time. And then, I hit a bump or two in the road. One of those bumps was more of a mountain than a bump, which didn’t help. But that was fine; I would survive!

After I recovered from that pretty miserable first year (a year that led me to reconsider if a PhD was for me), I got back on my PhD Pony and began to ride again.

I was picking up speed and making up for some of the time I’d lost in the first year’s Pity Party. The way I saw it was that I could still submit within three months of my three years. Yeah, that would be good. I could be happy with that.

And then, I hit a bump or two in the road. I was feeling overwhelmed and stressed. And then I got sick. And then there were more social stresses. And then I broke my ankle. And then, and then, and then… And let’s not forget about the second bout of extreme self-doubt that led me to reconsider if a PhD was for me…

[Enter more excuses, rationalisations, and justifications here… Then enter a few more for good measure…]

But it was all fine. I was starting to feel confident again and, even though I would definitely miss my three-year [impossible] goal, I was going to submit within three months after the three years. Well, maybe four months. Five? Six…? OK, seven. Seven months. Definitely no more than seven months. Three years and seven months. And that’s it. Really. That. Is. It.

So here I am, three and a half years into my PhD and I am still writing.

Because I can’t do it. The work has been so very overwhelming and I have struggled to find a way through my massive mountain of data. And it doesn’t help that my own physical health has been less-than-brilliant which has added to my stress, creating a crazy cycle of, well, crazy. (You can read about my May madness on my personal blog.)

However, I have been working some new approaches to my writing, and to my entire work-life balance system. And I think I am finally starting to gain some traction. Some of those changes mean that I am spending less time in front of a computer but, happily, I am a more productive when I am working on a computer.

Over the next week or two, I will be busily (and manically!) working on completing my findings chapters which has been a massive, ugly, furry beast of a task. But if my new approach to work (and data analysis) continues to go smoothly, I should be able to succeed in this goal.

I am hoping (desperately!) that I will not face as many challenges when I start putting together the rest of my thesis. Because let’s be honest, my supervisors (as wonderful as they are) are probably getting really fed up with my ongoing delays!

And that, in a rambling nutshell, is why I am still writing. (But hopefully not for long!)

Published: A Gen-X perspective of online information and reputation management

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My paper, ‘Managing and evaluating personal reputations on the basis of information shared on social media: a Generation X perspective’, has been published in Information Research. The paper is co-authored with my PhD supervisors, Peter Cruickshank, Professor Hazel Hall, and Alistair Lawson and shares some early findings from my PhD research, specific to my Generation X data subset.

The paper was presented at the Information Seeking in Context (ISIC) 2016 conference in Zadar, Croatia, this past September. (Slides are available here and can also be found below.)

Some of the results shared in the paper indicate that:

  • Participants view their online identity (or identities) as representations of their offline personas. In some cases, personal and professional personas are kept separate by using different online platforms for different aspects of an individual’s offline life.
  • Self-censorship is a key tool in the management of reputation, with censorship activities varying based on the platform and perceived audience.
  • It can be difficult to identify information behaviours that elicit positive evaluations of others, yet negative evaluations can be made in an instant if someone shares information (for example, a tweet or Facebook post) that is in stark contrast to their own views and opinions.
  • The levels of intentional reputation management vary, and is more often concerned with how the information will be received by others, rather than the impact on their own reputation.

The full study is expected to be completed in spring 2017. The full results will combine the Generation X subset with data gathered from an equal number of Generation Y and Baby Boomer participants. At that time, the three datasets will (most likely) be combined to discuss information behaviours based on the four research questions as a whole, rather than as generation groups. However, I hope to be able to pull at least some generational-based data for future small reports, papers, or posters.

The full text of the paper is available in Information Research, along with other papers from the ISIC conference. Below is an abstract and the presentation slides. Please do get in touch if you have any questions about this paper or my research as a whole.

Managing and evaluating personal reputations on the basis of information shared on social media: a Generation X perspective

Ryan, F., Cruickshank, P., Hall, H., Lawson, A. (2016). Managing and evaluating personal reputations on the basis of information shared on social media: a Generation X perspective. Information Research.

Abstract
Introduction. The means by which individuals evaluate the personal reputations of others, and manage their own personal reputations, as determined by information shared on social media platforms, is investigated from an information science perspective. The paper is concerned with findings from a doctoral study that takes into account prior work on the building and assessment of reputations through citation practice, as explored in the domain of scientometrics.

Method. Following the practice of studies of everyday life information seeking (ELIS), a multi-step data collection process was implemented. In total forty-five participants kept diaries and took part in semi-structured interviews. In this paper fifteen of these participants are represented.

Analysis. A qualitative analysis of the data was undertaken using NVivo10 to consider the information practices of one of three age group cohort generations: Generation X.

Results. Results generated from this initial analysis show some clear alignments with established knowledge in the domain, as well as new themes to be explored further. Of particular note is that social media users are more interested in the content of the information that is shared on social media platforms than they are in the signals that this information might convey about the sharer(s). It is also rare for these users to consider the impact of information sharing on personal reputation building and evaluation.

Conclusion. The analysis of the full dataset will provide further insight on the specific theme of the role of online information in personal reputation management, and contribute to theory development related to the study of information seeking behaviour and use.

A full set of data, at last!

dataThis week marked a very exciting, very important part of my PhD research: I completed my data collection! That means I now have a full set of data from 45 participants. Which is even more exciting for me, as I have experienced a few delays in my data collection.

At this stage, my participants have been divided into three sets: Generation Y (born 1981-1997), Generation X (born 1965-1980), and Baby Boomers (born 1946-1964). It is possible that I will divvy them up into narrower age groups for some or all of my findings, but this is where the groupings are at this time. Regardless, my intentions are to analyse my data through an age-based lens. (With an open mind to considering other ways of looking at the data.)

Each participant provided three general types of data: Some general background information about their education levels, employment, and social media history; information from a week’s worth of data collection; and the responses from their interviews. The background information will be used to help me classify my findings during the analysis stage and may help to determine sub-groups within the generations or other age bands. The data from diaries and interviews, however, will largely be treated as the same type of information—at least in the beginning.

Now that I have all of my data, I need to complete the transcription of the interviews. And then it will be time to code everything up before the all-important analysis stage. I will share a bit of insight into each of these steps as I go along.

Things are certainly looking up in my world of PhD dreams… and I am feeling more and more confident about those dreams becoming a reality. And that means that I will likely be sharing a bit more of my progress and thought processes with you. But for now … it’s time to crack open a bottle of Prosecco to celebrate this great research milestone!