A deeper look at the collective intelligence phenomenon

klaus Solberg Söilen

Abstract


For the upcoming conference on Intelligence Studies at ICI 2020 in Bad Nauheim, Germany the focus of this issue of JISIB is on collective intelligence and foresight. The first two papers by Søilen and Almedia and Lesca deal with collective intelligence from an intelligence studies perspective. It may be said that the Internet itself is a gigantic collective intelligence effort, the largest in human history. Open source is a prerequisite for this system to work for everyone. The article by Černý et al. is on open source. All other contributions are on the connection between the Internet, software and intelligence. This issue consists of seven articles to compensate for two articles that were taken out by editors in the last issue. The first article by Søilen entitled “Making sense of the collective intelligence field: a review” is a historical review of the field of collective intelligence. The paper shows how collective intelligence is an interdisciplinary field and argues there is a flaw in the notion of “wisdom of crowds”. Collective intelligence can be understood in terms of social systems theory and as such this approach has been fruitful for the social sciences, although so far not very popular. It also bares relevance for the study of business and economics. The second article by Almeida and Lesca is entitled “Collective intelligence process to interpret weak signals and early warnings”. Early warning and the detection of weak signals is a vital topic for any intelligence organization. Two aspects are discussed in the paper, the importance of new technology and collective sense making or interpretation The third article by Shaikh and Singhal entitled “Study on the various intellectual property management strategies used and implemented by ICT firms for business intelligence” deals with intellectual property rights and patenting strategies. The authors identify a number of defensive and offensive IP strategies applied to ICT companies. The results have a bearing on patent acquisitions. The fourth article by Lamrhari et al. is entitled “Web intelligence for understanding customer satisfaction: application of Latent Dirichlet Allocation (LDA) and the Kano model”. Customer satisfaction today is mostly measured with data from the internet, using different business intelligence techniques. The Kano model is still valuablei,ii, but the way we gather information to assess the different levels in the model has changed. The authors use Latent Dirichlet Allocation to analyze the voice of customer (VOC) in online reviews. They suggest that BI techniques and a fuzzy-Kano model can enable companies to better understand their customers’ online reviews. The fifth article by Nahili et al. is entitled “A new corpus-based convolutional neutral network for big data text analysis”. Companies need efficient ways to analyze everything that is said about them on the internet (reviews, comments). The paper suggests a convolutional neural network (CNN) as it has been successfully used for text classification. IMDB movie reviews and Reuters datasets were used for the experiment. The sixth article by Černý et al. is entitled “Using open data and google search data for competitive intelligence analysis”. Taking the Czech antidepressant market as an example, the authors show how competitive intelligence can be obtained using Google Search data, Google Trend and other OSINT sources. The seventh article by Dadkhah et al. is entitled “The potential of business intelligence tools for expert findings”. The paper suggests a way for researchers to find experts using business intelligence tools. The same method may also be used by any business or person looking for experts on a specific topic. As always, we would above all like to thank the authors for their contributions to this issue of JISIB. Thanks to Dr. Allison Perrigo for reviewing English grammar and helping with layout design for all articles and to the Swedish Research Council for continuous financial support.
We hope to see you all at the ICI 2020 on the 16-17 March, 2020. The deadline for the two-page abstract submission is March 1st, 2020.


Keywords


Collective intelligence

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References


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