AJIC Issue 15, 2015

Permanent URI for this collectionhttps://wiredspace.wits.ac.za/handle/10539/19266

There is already extensive scholarly publishing on informatics and ICT4D, charting the contours of early stage digital transformation in Africa. This issue of The African Journal of Information and Communication (AJIC) publishes a collection of articles developed from papers presented at the 44th Southern African Communications Lecturers Association (SACLA) Conference, held on 2 and 3 July 2015 at Open, Maboneng Precinct, Johannesburg. The theme of the conference was “Renewing ICT teaching and learning: Building on the past to create new energies”. The emphasis on renewal offers an important message to academics and universities to push forward with change, in an era where change inertia has set in in many parts of the higher education environment and where a reminder is needed that, in the 21st century, change is the only constant. Digital technologies will only create value in the university experience when used for active innovation in teaching and learning, rather than passive availability. Investment in university Internet access, where most ICT spending has historically focused, offers only the foundation for educational informatics, not the digital learning experience. Educational futures require investment in the creative side of digital media use for teaching, learning and research. Issue 15 also publishes a range of unsolicited articles relevant to this thematic area, carefully reviewed, revised and edited. These articles illustrate the breadth of the field of informatics and its importance for future development, as well as the new research problems in the fields of informatics and ICT4D.

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Has files: YesAuthor: search.filters.author.Johnston, KevinSubject: search.filters.subject.twitter moods, predict, stock exchange index movement, big data analytics, Africa and developing countries.

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    Critical Insights Into the Design of Big Data Analytics Research: How Twitter “Moods” Predict Stock Exchange Index Movement
    (LINK Centre, University of the Witwatersrand (Wits), Johannesburg, 2015-12-15) Maree, Stiaan; Johnston, Kevin
    The research explored whether one or more of the South African Twitter moods could be used to predict the movement of the Johannesburg Stock Exchange (JSE) All Share Index (ALSI). This is a proof of principle study in the field of big data analytic research in South Africa, which is at a relatively early stage of development. The research methods used secondary data from Twitter’s application programming interfaces (APIs), and formulated a model to extract public mood data and search for a causal effect of the mood on the closing values of the JSE ALSI. Over three million tweets were gathered and analysed over a 55-day period, with data collected from the JSE for 39 weekdays, from which only one variable (mood states) was considered. Four of the South African Twitter mood states did not produce any correlation with the movement of the JSE ALSI. The mood Depression had a significant negative correlation with the same day’s JSE ALSI values. The major finding was that there was a highly significant positive correlation between the Fatigue mood and the next day’s closing value of the JSE ALSI, and a significant causality correlation from the Fatigue mood to the JSE ALSI values. The findings support the behavioural finance theory (Wang, Lin & Lin, 2012), which states that public mood can influence the stock market. Organisations and governments could use Twitter data to gauge public mood and to ascertain the influence of public mood on particular issues. However, very large data sets are required for analytical purposes, possibly five to ten years of data, without which predictability is likely to be low.