Engineering social media driven intelligent systems through crowdsourcing: Insights from a financial news summarisation system

作者: Martin Sykora

DOI: 10.1108/JSIT-03-2016-0019

关键词:

摘要: Purpose The purpose of this paper is to explore implicit crowdsourcing, leveraging social media in real-time scenarios for intelligent systems. Design/methodology/approach A case study using an illustrative example system, which systematically used a custom platform automated financial news analysis and summarisation was developed, evaluated discussed. Literature review related crowdsourcing collective intelligence systems also conducted provide context further the study. Findings It shown how, that useful can be constructed from appropriately engineered platforms are integrated with processes. A recent inter-rater agreement measure evaluating quality crowd contributions explored found value. Practical implications This argues when closely other processes into single may highly worthwhile online approach through crowdsourcing. Key practical issues, such as achieving high-quality contributions, challenges efficient workflows integration systems, were Important ethical considerations covered. Originality/value A contribution existing theory made by proposing how Web benefit As opposed traditional platforms, presented system has set elements encourages Instances media, Twitter, often called piggybacking, have been past; however, entirely custom-built relatively novel several advantages. Some discussion construction contribute body literature field.

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