1,721,240 research outputs found
Leading Meaningful Change
No full textThis innovative book combines psychological insights with cutting-edge data analysis to demonstrate how effective communication can drive both organizational and personal transformation. It delves into psychological and emotional barriers to change, offering strategies to overcome resistance and foster collaboration by addressing both emotional and rational aspects of change.
Adopting a multidisciplinary approach, Andrea Fronzetti Colladon and Francesca Grippa provide a comprehensive understanding of change dynamics in both personal and organizational contexts. The book outlines a structured framework with practical tools, exercises, and strategies for managing the complexities of change. Leading Meaningful Change examines the critical role of “honest signals” in change dynamics, revealing the power of innovative methods from artificial intelligence, network analysis, and text mining. The book also explores how artificial intelligence and big data are reshaping change management processes, discussing their role as both disruptors and solution providers in organizational strategies.
Leading Meaningful Change will greatly benefit students and scholars in business and management, sociology, social psychology and innovation. It is also an essential tool for practitioners in business leadership and occupational psychology seeking to drive meaningful, lasting change
Designing Networks for Innovation and Improvisation. Proceedings of the 6th International COINs Conference
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The Semantic Brand Score
No full textThe Semantic Brand Score (SBS) is a new measure of brand importance calculated on text data, combining methods of social network and semantic analysis. This metric is flexible as it can be used in different contexts and across products, markets and languages. It is applicable not only to brands, but also to multiple sets of words. The SBS, described together with its three dimensions of brand prevalence, diversity and connectivity, represents a contribution to the research on brand equity and on word co-occurrence networks. It can be used to support decision-making processes within companies; for example, it can be applied to forecast a company's stock price or to assess brand importance with respect to competitors. On the one side, the SBS relates to familiar constructs of brand equity, on the other, it offers new perspectives for effective strategic management of brands in the era of big data
Big data analysis of economic news
No full textWe propose a novel method to improve the forecast of macroeconomic indicators based on social network and semantic analysis techniques. In particular, we explore variables extracted from the Global Database of Events, Language, and Tone, which monitors the world’s broadcast, print and web news. We investigate the locations and the countries involved in economic events (such as business or economic agreements), as well as the tone and the Goldstein scale of the news where the events are reported. We connect these elements to build three different social networks and to extract new network metrics, which prove their value in extending the predictive power of models only based on the inclusion of other economic or demographic indices. We find that the number of news, their tone, the network constraint of nations and their betweenness centrality oscillations are important predictors of the Gross Domestic Product per Capita and of the Business and Consumer Confidence indices
Being known for something good: measuring organizational reputation through semantic network analysis
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