Fall and redemption: Monitoring and engaging in social media conversations during a crisis

Social media content can spread quickly, particularly that generated by users themselves. This is a problem for businesses as user-generated content (UGC) often portrays brands negatively and, when mishandled, may turn into a crisis. This paper presents a framework for crisis management that incorporates insights from research on social media users’ behaviour. It looks beyond specific platforms and tools, to develop general principles for communicating with social media users. The framework’s relevance is illustrated via a widely publicised case of detrimental UGC. The paper proposes that, today, businesses need to identify relevant social media platforms, to monitor sentiment variances, and to go beyond simplistic metrics with content analysis. They also need to engage with online communities and the new influencers, and to respond quickly in a manner that is congruent with said social media platforms and their users’ expectations. The paper extends the theoretical understanding of crisis management to consider the role of social media as both a cause and a solution to those crises. Moreover, it bridges information management theory and practice, providing practical managerial guidance on how to monitor and respond to social media content, particularly during fast-evolving crises

Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

Micro, Meso, and Macro Data Collection and Analysis, as a Method for Speculative and Artistic Exploration

In this work, an attempt is made to explore the emerging computationally-enhanced private and public environments by analyzing their ecological transitions and its implications on practical, aesthetic, and speculative dimensions. The author has decided to methodologically dissect the multiplicity of information that exists on many possible-to-detect scales (micro, meso, macro), and utilize this extraction as a tool for experimentation and redefinition. With the use of custom-made hardware and software utilities (sensor devices, sentiment analysis algorithms, online APIs, and many more), a vast amount of data is collected and used as a multidimensional layered architecture that constantly shifts and transforms. The extracted and analyzed content of the collection becomes the essence of the work that is shaped and refined through digital and physical making – middleware, recursion, mapping – and by utilizing technological objects within the physical space, the creative process is augmented and amplified, exploring not only new practices and novel applications, but rather redefining behavior, thought-process, and context