1,720,993 research outputs found
Brand Intelligence Analytics
No full textLeveraging the power of big data represents an opportunity for brand managers to reveal patterns and trends in consumer perceptions, while monitoring positive or negative associations of the brand with desired topics. This chapter describes the functionalities of the SBS Brand Intelligence (SBS BI) app, which has been designed to assess brand importance and provide brand analytics through the analysis of (big) textual data. To better describe the SBS BI’s functionalities, we present a case study focused on the 2020 US Democratic Presidential Primaries. We downloaded 50,000 online articles from the Event Registry database, which contains both mainstream and blog news collected from around the world. These online news articles were transformed into networks of co-occurring words and analyzed by combining methods and tools from social network analysis and text mining
The digital footprint of innovators: Using email to detect the most creative people in your organization
No full textWe propose a novel method for finding the most innovative people in an organization, using email to analyze structure and dynamics of the organization’s online communication. To illustrate our approach, we analyzed the email archive of 2000 members of the R&D department of a US multinational company. We use metrics of social network analysis extended with meta-data of interaction dynamics to calculate features for individual employees: their network positions, messages sent and received, pings to others and response times. We find a distinction between innovation group leaders and subject matter experts focused on publishing papers and patents. Innovation administrators have a higher number of direct contacts, are more committed in conversations and receive more messages than they send. We also found significant differences between innovators oriented towards internal awards and innovators more concerned with external recognition of their work
Fantastic Interfaces and Where to Regulate Them: Three Provocative Privacy Reflections on Truth, Deception and What Lies Between
No full textSpeech Interfaces represent a new interactive phenomenon, which entails massive personal data processing. The spectrum of legal issues that arises from this interaction impacts both user privacy and social relationships. This study addresses three potential issues or ‘provocations’ relating to speech interaction that illustrate the challenges and complexity of this socio-legal domain: (i) the potential for lying; (ii) the possibility of breaching the law; (iii) the ability to interpret an order. It deploys an in-depth analysis of the related legal consequences and implications with the scope to prompt discussion around these provocative issues. It first provides an overview of the correct hermeneutical approach to frame legal paradigms, highlighting the crucial legal aspects, conceptual approaches and interpretations to be considered when addressing the whole ‘interactive artificial agents’ (IAA) phenomenon. The study adopts the classical Civil Law system’s methodology (qualitative/top-down analytical). The core of the study then focuses on the three provocations as connected by personal data processing. The goal is to provide a critical legal analysis of those interfaces that could impact the foundation of human socio-legal interrelations. By raising awareness of these controversial aspects, the work contributes to fostering further discussion about interdisciplinary privacy issues that stand at the intersection of Law, Social Sciences and HCI design, and that cross-pollinate each other
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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