In this paper we present visual methodologies attuned to the networked nature of digital images. First, we describe approaches to image research in which images are not separated from their network, but rather studied 'en groupe'. Here, we contrast approaches that treat images as data, and those that regard images as content. Second, we focus on the production of images for digital research, presenting three of their functions: a) the creation of diagrams that facilitate collaboration in interdisciplinary research teams; b) the use of visualizations for cross-platform image analysis; and c) designing images for public participation. Most importantly, such visualizations are not used to form the esthetic culmination of analytical work, but are rather functional tools for digital research that serve parts of the entire research process, from its formulation and operationalization to the engagement of a broader public.
MULTIFILE
This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at the core of the proposed DSS that enables to monitor, estimate, and classify clients’ sentiments in terms of polarity, as expressed in public comments on social media (SM) company channels. The SAE is built on machine learning (ML) text classification models that are cross-source trained and validated with real data streams from a platform like Trustpilot that specializes in user reviews and tested on unseen comments gathered from a collection of public company pages and channels on a social networking platform like Facebook. Such crosssource opinion analysis remains a challenge and is highly relevant in the disciplines of research and engineering in which a sentiment classifier for an unlabeled destination domain is assisted by a tagged source task (Singh and Jaiswal, 2022). The best performance in terms of F1 score was obtained with a multinomial naive Bayes model: 0,87 for validation and 0,74 for testing.
DOCUMENT
This is a report of the research done during the Summer School 2022 at the Digital Methods Initiative (UvA). The work and the report were developed in collaboration with the participants in the datasprint: Gabrielle Aguilar // Federica Bardelli // Laura Bruschi // Miranda García // Giulia Giorgi // Matthew Hanchard // Bakar Abdul-Rashid Jeduah // Natalie Kerby // Goran Kusić // Bruno Mattos // Samir van Oeijen Rodríguez // Alessandro Quets // Eivind Røssaak // Miazia Schueler // Zijing Xu // Xin Zhou // Chloe Sussan-Molson // Maud Borie // Alireza Hashemzadegan // Misha Velthuis. Abstract:Sea-level rise has long been one of the most locally tangible impacts of climate change, both now and in the future. Due to accelerating climate change, the annual rate of sea-level rise has almost tripled over the last century, and the mean sea level rise is expected to rise 0.3m-1.0m by 2100 (Duijndam et al., 2021). The IPCC states that risks include increased flooding, erosion, loss of ecosystems and permanent submergence (Oppenheimer et al., 2019). In the UK, there are fierce debates over whether to protect or surrender coastal homes threatened by sea-level rise (Fisher, 2022), while in the Netherlands the trust in its strong water management and engineering tradition has led to the so-called myth of the dry feet—the idea that sea-level rise in the Netherlands, a country that in part lies below sea-level, can be countered by merely building higher dams (Schuttenhelm, 2020). Scenarios for the future of the Netherlands include new adaptation strategies of living with the water, in which parts of the land are given back to nature to preserve larger cities (Deltares, 2019). Globally, some of the world’s most populous cities, such as New York, Bangkok and Shanghai are amongst the most vulnerable (C40 Cities, 2018), while the existential threats to small islands such as Kiribati, Seychelles and the Maldives could result in entire states disappearing from the world (Martyr-Koller et al., 2021). Emblematic images of people wading through the flooded streets of Venice holding up their shopping bags or stopping for a coffee travelled the news and social media outlets as an illustration of the climate crisis, and the collision of rising sea levels, a sinking city, surging seasonal winds and failing governance as the city experienced its worst floods in 50 years (National Geographic, 2019).There have been some notable efforts to visualise scientific projections of sea-level rise (e.g. Climate Central, 2015), as well as more creative attempts to communicate the threat such as the iconic Der Spiegel depicting a submerged Koln Cathedral (Mahony, 2016). Yet it is argued that sea-level rise remains a relatively low public concern given the huge potential risks to ecosystems and human habitats (Akerlof et al., 2017), while a recent advanced review of digital media research on climate communication found no research focused on the issue (Pearce et al., 2019). In this project, we will try to fill this gap, looking to see how both present and future sea-level rise is being imagined and interpreted on social media platforms, in terms of textual and visual content, information sources, locations, and point in time (i.e., future or present).
MULTIFILE
This paper focuses on the topical and problematic area of social innovations. The aim of this paper is to develop an original approach to the allocation of social innovations, taking into account characteristics such as the degree of state participation, the scope of application, the type of initiations as well as the degree of novelty, which will be elaborated on further in this article. In order to achieve this goal, the forty-two most successful social innovations were identified and systematized. The results of this study demonstrated that 73.5% of social innovations are privately funded, most of them operating on an international level with a high degree of novelty. Moreover, 81% of all social innovations are civic initiatives. Social innovations play an important role in the growth of both developed and less developed countries alike as highlighted in our extensive analysis
DOCUMENT
Visual cross-platform analysis (VCPA) is a methodological approach designed to overcome two forms of bias in the social media research literature: first, a bias towards studies of single plat- forms and, second, a bias towards analysis that focuses on text and metrics. VCPA addresses this by providing methods for identifying visual vernaculars, defined as the platform-specific content and style of images that articulate any given social or political issue.
IMAGE
This article interrogates platform-specific bias in the contemporary algorithmic media landscape through a comparative study of the representation of pregnancy on the Web and social media. Online visual materials such as social media content related to pregnancy are not void of bias, nor are they very diverse. The case study is a cross-platform analysis of social media imagery for the topic of pregnancy, through which distinct visual platform vernaculars emerge. The authors describe two visualization methods that can support comparative analysis of such visual vernaculars: the image grid and the composite image. While platform-specific perspectives range from lists of pregnancy tips on Pinterest to pregnancy information and social support systems on Twitter, and pregnancy humour on Reddit, each of the platforms presents a predominantly White, able-bodied and heteronormative perspective on pregnancy.
DOCUMENT
Objectives Most complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions. Methods A scoping review was conducted using the Arksey and O’Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics,level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting. Results Among 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results. Conclusion SNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.
DOCUMENT
The range of studies that has been conducted on the role of gossip in organizations suggests that gossip in the workplace plays a variety of important roles in organisational processes. However, relatively few studies have explored its role in intercultural situations. This is surprising given how organisations are becoming increasingly diverse. This paper addresses this gap in the literature. It reports on an exploratory project that sought to determine how perceptions of organisational gossip vary between members of different cultural groups. Using a sensemaking, interpretative approach, we showed two gossip scenarios to 8 Chinese, 8 German and 8 Dutch first year students, and conducted semi structured interviews, asking them how they perceived the nature of the gossip, the gossiper and the object of gossip (i.e., the person being gossiped about). After analysing the data with ATLAS.ti, we observed certain patterns emerging. For example, while all students condemned a manager’s bad behaviour, the Chinese students seemed to expect it more than did their Dutch or German counterparts. Moreover, we found that the relationship and amount of trust that exists between gossiper, listener and object of gossip greatly influenced how the gossiper and object of gossip were perceived. After reflecting on our research methodology, this study sets the stage for the next phase of our research on the role of gossip in intercultural situations. LinkedIn: https://www.linkedin.com/in/dominiquedarmon/
DOCUMENT
Background: Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Objective: The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Methods: This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization’s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy. Results: Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations’ inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects.
DOCUMENT
ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform online dashboard monitoring online hate speech. The case under study is the project for the European Observatory of Online Hate (EOOH). Results: We outline the process taken for design and prototype development for which a design thinking approach was followed, including multiple potential user groups of the dashboard. The paper presents this process's outcome and the dashboard's initial use. The identified issues, such as obfuscation of the context or identity of user accounts of social media posts limiting the dashboard's usability while providing a trade-off in privacy protection, may contribute to the discourse on privacy and data protection in (big data) social media analysis for practitioners. Research limitations/implications: The results are from a single case study. Still, they may be relevant for other online hate speech detection and monitoring projects involving big data analysis and human annotation. Practical implications: The study emphasises the need to involve diverse user groups and a multidisciplinary team in developing a dashboard for online hate speech. The context in which potential online hate is disseminated and the network of accounts distributing or interacting with that hate speech seems relevant for analysis by a part of the user groups of the dashboard. International Information Management Association
LINK
