Month: September 2017

PhD Judged “Top 5” Internationally for Information Science.

Surprised and delighted to be informed that my PhD has been judged in the “Top 5″ Internationally in 2017 for Information Science in the ProQuest Doctoral Dissertation Award.

My thesis topic was Re-examining and re-conceptualising enterprise search and discovery. The Association for Information Science and Technology (ASIS&T) scope includes any PhD related to, “the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes.”

The judges comments include: “As far as I know, this is the first comprehensive and holistic work studying enterprise search; this is a pretty relevant theme and the contributions of the thesis are sizeable” and “Findings from this thesis have direct implications for the theories and practices in information science”.

A big thanks to my supervisory team of Professor Simon Burnett (Robert Gordon University) and Dr Laura Muir (Edinburgh Napier) along with everyone who has helped and encouraged me. It further motivates me to continue academic research in this area and to make further contributions to the discipline in what is a tremendously exciting time.



Applying sentiment analysis to oil & gas company reports.

Sentiment Analysis

I presented at the International Society of Knowledge Organization (ISKO) this week, sharing findings of an exploratory study. A Knowledge Organization System (KOS) was automatically applied to the annual company reports of four similar sized oil and gas companies to detect forward-looking strong and hesitant sentiment, in order to detect rhetoric, social phenomena and predict future business performance.

The “Discovery” part of “Enterprise Search & Discovery” is arguably downplayed in much of the existing academic and practitioner literature. In addition to finding what you know exists (or finding document ‘containers’ that you did not), there may be a case to embed various sentiment algorithms as standard in enterprise search & discovery technology deployments. Designing with ‘serendipity in mind’, this may move the intent of a deployment from one of pure retrieval, to one of pattern recognition. Where ‘trace fossils’ may exist in the information aggregate, not discernible from any single document.

The utilization of such algorithms to ‘compare’ and ‘contrast’ perhaps in a web part in the user interface, may move the enterprise search & discovery tool further up the Bloom’s Taxonomy pyramid, in assisting higher forms of thinking (along with delivering the surprising). It may not make sense for many queries made in general purpose ‘Google-like’ search tools deployed behind a company’s firewall, but detecting queries which do could be a useful undertaking. As described in a previous post many things can have a ‘sentiment’ which may act as a catalyst for further inquiry and potential new learnings. Whilst sentiment analysis is a useful technique when you have an a priori hypothesis in mind, it could well surface interesting phenomena even when you don’t.

Click here for link to presentation

Automated Forward-looking Sentiment Analysis, Search Engine Bias and Cognitive Search in Geoscience

Just a quick update on what I have been up to these past few hectic months as my last blog post was back in May this year. Below are some papers I have been working on over the summer and upcoming conferences I will be presenting at:

Golden Gate.JPG

Conducted some research recently in California (more on this in later posts)

Sentiment Analysis in organizational reports

I will be presenting on the 11th September in London at the ISKO conference in a collaboration with Laura Muir (Associate Professor of Information Systems at Edinburgh Napier University). The topic will be applying automated sentiment analysis to identify forward-looking sentiment(about the future) in company reports. This provides an indicator of how confident an organization feels about the future and may be dosed with rhetoric. We used biologically inspired word diversity algorithms which to our knowledge have not been used before to assess forward-looking sentiment. We also investigated predictive links to future financial performance and organizational phenomena such as the reaction to a crisis. I hope to share the presentation and paper shortly in the public domain. I think there are some very exciting findings and opportunities for companies to develop new knowledge as well as conduct further research:

Search Engine Bias

Information Today published an extended article I wrote on search engine bias in their Sep/Oct 2017 edition here: . It is an extension of the blog post I made earlier this year including links to ‘fake news’ and bias within enterprise search & discovery technology. Information Today requires a subscription for the latest issues.

Cognitive Search Assistants in the Geosciences

Delighted that my paper on Cognitive Search Assistants in the Geosciences was accepted for the Annual Meeting of the Geological Society of America (GSA) in Seattle during October 2017. This builds on and further extends existing research I published previously on this site: , and work I presented a few years ago in Turkey . These tools and techniques move beyond traditional deductive inference, to include both an inductive and abductive inference focus. I will be sharing the presentation and paper in the public domain later in the year.