Crowdsourcing Project Research Articles

Sustainable Development of Digital Cultural Heritage: A Hybrid Analysis of Crowdsourcing Projects Using fsQCA and System Dynamics

Cultural heritage crowdsourcing has emerged as a promising approach to address the challenges of digitizing and preserving cultural heritage, contributing to the sustainable development goals of cultural preservation and digital inclusivity. However, the long-term sustainability of these projects faces numerous obstacles. This study explores the key configurational determinants and dynamic evolutionary mechanisms driving the sustainable development of cultural heritage crowdsourcing projects, aiming to enhance their longevity and impact. An innovative integration of fuzzy-set qualitative comparative analysis (fsQCA) and system dynamics (SD) is employed, drawing upon a “resource coordination–stakeholder interaction–value co-creation” analytical framework. Through a multi-case comparison of 18 cultural heritage crowdsourcing projects, we identify necessary conditions for project sustainability, including platform support, data resources, knowledge capital, and digitalization performance. The study reveals multiple sufficient pathways to sustainability through configurational combinations of participant motivation, innovation drive, social capital, and social impact. Our system dynamics analysis demonstrates that crowdsourcing project sustainability exhibits significant nonlinear dynamic characteristics, influenced by the interaction and emergent effects of the resource–participation–performance chain. This research offers both theoretical insights and practical guidance for optimizing crowdsourcing mechanisms and sustainable project operations, contributing to the broader goals of sustainable cultural heritage preservation and digital humanities development. The findings provide a roadmap for policymakers and project managers to design and implement more sustainable and impactful cultural heritage crowdsourcing initiatives, aligning with global sustainability objectives in the digital age.

Crowdsourcing Projekt „Reden Sie mit!“

Crowdsourcing project “Have your say!” – Practical research priorities for occupational medicine in Austria The aim of the AAMP project “Unresolved issues in occupational medicine. Have your say!” was to find out which topics should be prioritized with the limited research resources available in Austria. With the help of crowdsourcing, where, in contrast to traditional research practices, end users rather than scientists set the research topics, a practical research agenda with eight key topics was developed for Austria.

The Memorial Afterlives of Online Crowdsourcing

From May 2014 to March 2019 the Imperial War Museums launched a large-scale digital crowdsourcing project, ‘Lives of the First World War’. ‘Lives’ melded official and unofficial datasets to create an integrated database of people who had participated in the First World War. Over the course of the project 7.7 million individual histories were collected. After the initial collection phase, ‘Lives’ became a permanent digital memorial and database. This article investigates how ‘Lives’ contributed to public understandings of the First World War during and after its centenary. While undoubtedly an impressive and difficult undertaking, this article suggests that large scale data collection as a methodology on its own will replicate collection biases, unless married with specific collection drives. In the case of the First World War, this means that global majority narratives are subsumed by white British ones, at the expense of historically realistic data. The skewed datasets that come from large crowdsourced projects have widespread implications for cultural memories of events if they are to be digitally preserved within national collections.

Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs

Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity-variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity-estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs-indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.

The importance of theory at the Information Systems Journal

The importance of theory at the <i>Information Systems Journal</i>

On the roles of form systematicity and sensorimotor effects in language processing.

Grounded or embodied cognition research has employed body-object interaction (BOI; e.g., Pexman et al., 2019) ratings to investigate sensorimotor effects during language processing. We investigated relationships between BOI ratings and nonarbitrary statistical mappings between words' phonological forms and their syntactic category in English; i.e., form systematicity. In Study 1, principal components analysis revealed that BOI and form systematicity measures load on a common component, indicating they convey similar information about the probability of a word belonging to a particular syntactic category. In Studies 2, 3, and 4, form systematicity measures were stronger predictors of English Lexicon Project (ELP; Balota et al., 2007), Auditory English Lexicon Project (AELP; Goh et al., 2020), and English Crowdsourcing Project (ECP; Mandera et al., 2020) performance than BOI. In Study 5, BOI was a stronger predictor of performance from the Calgary Semantic Decision Project (CSDP; Pexman et al., 2017) than form systematicity. In Study 6, only form systematicity significantly predicted performance from the LinguaPix object naming megastudy (Krautz & Keuleers, 2022). Together, these results demonstrate that nonarbitrary statistical relationships in the form of mappings between ortho-phonological information and meaning are accessed automatically during language processing; i.e., even when syntactic category is not relevant to the task, and that sensorimotor simulation mechanisms are only strongly engaged when explicitly demanded by the task. We discuss the implications of these findings for proposals of embodied or grounded cognition and interpretations of neuroimaging data from word recognition tasks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Mobile crowdsourced test report prioritization based on text and image understanding

AbstractIn the process of mobile crowdsourced testing, a large number of test reports are generated, which often consist of short text and rich image information. One of the critical issues is how to review these reports efficiently. Researchers have recently proposed clustering, classification, and prioritization techniques to solve this problem. However, existing studies directly use related technologies to text description and segment the text content without further understanding of the text content. By deeply digging into the text information and distinguishing it according to its actual meaning, the sentences described in the text can be categorized into two types: Describing abnormal system behavior and describing reproduction steps. This paper proposes a mobile crowdsourced test report prioritization technique to improve performance. First, we use a TextCNN trained on large‐scale projects to distinguish the text descriptions of reports, then extract features from the text and screenshot information, respectively. Then we apply a clustering technique to gather similar reports. Finally, the inspection order is sampled from the clustering results. To validate our approach, we conduct experiments on six industrial crowdsourced projects. The results show that our method can detect all bugs faster in a limited time than existing prioritization methods, which can improve the bug reports review efficiency.

A crowd-sourced genomic project to assess hybrid content in a rare avian vagrant (Azure Tit Cyanistes cyanus (Pallas, 1770))

The aim of this study was to correlate plumage variation with the amount of genomic hybrid content in hybrids between Azure Tits Cyanistes cyanus (Pallas, 1770) and European Blue Tit Cyanistes caeruleus (Linnaeus, 1758), by re-sequencing the genomes of museum specimens of non-hybrids and presumed hybrids with varying plumages. The project was funded by crowdsourcing and initiated when two presumed Azure Tits, observed by hundreds of Swedish birdwatchers, were rejected as hybrids based on minor plumage deviations assumed to indicate hybrid contents from the European Blue Tit. The results confirm that hybrids with intermediate plumages, so called Pleske’s Tits, are first generation hybrids (F1 hybrids). Individuals, whose plumages are similar to Azure Tits, but assessed as hybrids based on minor plumage deviations, are all backcrosses but vary in their degree of hybrid content. However, some individuals morphologically recognized as pure Azure Tits expressed similar degrees of hybrid content. The results indicate that: (1) hybrid content may be widespread in Azure Tits in the western part of its habitat distribution; (2) plumage deviation in backcrosses is not linearly correlated with the genetic degree of hybrid origin; and (3) all Azure Tits observed in Europe outside its natural distribution may have some degree of hybrid origin. We therefore suggest that it is very difficult to phenotypically single out hybrids beyond first generation backcrosses. We argue that decreased sequencing costs and improved analytical tools open the doors for museomic crowd-sourced projects that may not address outstanding biological questions but have a major interest for lay citizens such as birdwatchers.

Editorial: Politics is not a spectator sport: On the role of psycholinguists in a global crisis

Editorial: Politics is not a spectator sport: On the role of psycholinguists in a global crisis

The role of system‐use practices for sustaining motivation in crowdsourcing: A technology‐in‐practice perspective

AbstractThe success of crowdsourcing (CS) systems depends on sustained participation, which is an ongoing challenge for the majority of CS providers. Unfortunately, participants are frequently demotivated by technical difficulties and the incorrect use of CS systems, which can result in CS failure. Although the literature generally assumes that sustained participation in CS is determined by a shift between intrinsic and extrinsic motivation, the role of system‐use practices in facilitating such a shift remains unknown. We explore how CS system‐use practices influence participants' sustained motivation, evolving from initiation to progression to sustention. Using the notion of technology‐in‐practice as a lens, we develop and examine a process model using an in‐depth case study of a large‐scale ongoing CS project, the Australian Newspaper Digitisation Program. The findings suggest that CS participants' motivation is shaped by an evolving combination of three basic components (i.e., contextual condition, outcome and action intensity) and mediated by two types of system‐use practice (i.e., passive and active). Passive‐use practices facilitate sustaining motivation from initiation to progression, whereas active‐use practices have a key role in sustention. Our study contributes to the emerging literature on the substantial role of system‐use practices in sustaining motivation, resulting in sustained participation. The findings also offer actionable insights into improving the viability of CS systems in retaining and motivating continuous and increased contributions from participants.

A Crowd-Sourcing Project to Understand, Prevent and Manage Incidences of Injury and Wounding to Astronauts and Off-Earth Colonists

Recent technical successes of the unmanned Mars 2020, Tianwen-1 and Hope Mars missions have further increased our hunger for space exploration and the possible colonisation of Mars is now firmly on the mid-term horizon. Furthermore, renewed commitment to settle on the Moon is anticipated within the next three years, led by NASA’s Artemis programme utilising the pan-space agency constructed lunar Gateway or Space X’s Starship system. These programmes will necessitate a larger number of astronauts spending longer periods in space and despite rigorous risk identification and mitigation procedures, injury is an inevitable consequence and management procedures will demand efficient and effective implementation. We have employed Cognitive Work Analysis to derive an abstraction hierarchy for reducing the potential for physical injury and managing the consequence of injury in space. We have used a crowd-sourcing approach to cluster factors and themes which may emanate from within or without habitat and consider solution management in the light of current and emerging technology. In addition, we also consider mental fitness as a confounder which may emerge during missions and propose methods for both measurement and management. Doi: 10.28991/HEF-2022-03-03-04 Full Text: PDF

A case study in citizen environmental humanities: creating a participatory plant story website

Public engagement in crowd-sourced science projects such as iNaturalist or the Audubon Christmas Bird Count is a long-established practice within environmental studies and sciences. As a corollary to these “citizen science” efforts, “citizen humanities” engages public participation in humanities research and/or with humanities tools such as creative writing, photography, art-making, or conducting and recording interviews. In this essay, we outline our work creating a citizen environmental humanities website, Herbaria 3.0, including our motivations, process, and theoretical underpinnings. This project draws upon the critical understanding within environmental studies of the importance of narrative and storytelling for fostering a connection and commitment to environments and nonhuman beings. Situated within the field of environmental humanities, our website solicits, collects, and archives stories about the manifold relationships between plants and people, inviting visitors to read, share, or write their own story for digital publication. The kind of environmental storytelling that results, we argue, can (1) enrich our conceptualization of attachment to places, (2) expand our notion of what “counts” as an encounter with nature, and (3) help us recognize the agency of individual plants. We conclude that similar citizen humanities projects are crucial to the ongoing work of environmental humanities and environmental studies at large, for it is through such public engagement that we can meet the cultural challenges that seeded, and the societal problems occasioned by, ongoing climate change.

Mapping Antarctic and Arctic Women: An exploration of polar women’s experiences and contributions through place names

Abstract In this commentary, I investigate the Poles differently, and in situ, rather than only as stereotypically barren uninhabited expansive places on a globe or maps. The human stories are behind the relatively white space on which few place names are marked. But the more visible ones are made and told through a male-dominated, colonial narrator and mapmaker, until more recently. Cartography, like history, has overwhelmingly documented men’s worlds, stories, dominations and accomplishments, creating a virtual whiteout of women’s and notably Indigenous women’s stories also in polar regions. In this commentary, I report on a journey into (re)mapmaking I did of women’s stories told through female place names and toponymies of women especially in the Antarctic, through a crowd-sourced project, Mapping Antarctic Women. I explore not only mapping female place names and women’s stories in the Arctic, exploring gendered, colonial and western culture mapping but also newer digital Indigenous place name mapping and also mapping of human-exacerbated changes in the ice that makes the Antarctic map.

Crash risk and subjective risk perception during urban cycling: Accounting for cycling volume

Most research concerned with cyclists’ safety has been focused on the crash risk (i.e. their objective safety). However, there has been a growing interest in the perceived level of this risk (i.e. the subjective safety of cyclists). Crash risk and subjective risk perception in urban cycling appear to be mostly well aligned. For example, reduced speed limits have been found to reduce both objective and subjective risks (although there is also evidence for some incongruences). This absolute number of incidents could be misleading, as it does not account for potential differences in cycling volume (i.e. cyclists are likely to prefer streets with reduced speed limits). Thus, it may be important to adjust the absolute number of incidents relative number to the local cycling volume. In this research, we investigate the relation of cycling crashes and subjective risk perception (operationalized through reports from a crowd-sourcing project) for different types of cycling infrastructure and different speed limits, while accounting for the local cycling volume. We find that the absolute number of VGI reports and crashes can be misleading: whereas the absolute incident numbers, for example, suggest few benefits of cycling lanes and tracks, adjusting for the cycling volume reveals an increase of both objective and subjective safety as compared to streets without cycling infrastructure. We also identify situations where cyclists apparently underestimate the crash risk (i.e. on cycleways opposing the cars’ traveling direction, and at streets with a speed limit of 30 km/h intersecting streets with higher speed limits). Additional research is required to understand the sources of these discrepancies, and how to make cyclists aware of them.

German in childhood and Latin in adolescence: On the bidialectal nature of lexical access in English

The nature of word etymology, long a topic of interest in linguistics, has been considered to a much lesser extent in the word recognition literature. The present study created a database of overlapping words from the English Lexicon Project (ELP) and a database with the age of acquisition (AoA) norms which were categorized as either Germanic or Latin-based. Results revealed that Germanic words were learned earlier than Latin-based words. Germanic words also showed slower reaction times and higher accuracy relative to Latin-based words even when controlling for AoA, word frequency, and length. Additionally, analyses were conducted using a publicly available database that used the English Crowdsourcing Project (ECP) data with native and second language (L2) English speakers. The results with native speakers were similar to those collected with the ELP. However, nonnative speakers showed better accuracy and faster reaction times for Latin-based words compared to Germanic words. The findings support a bidialectal view of English in that Germanic words serve as the base of lexical processing during childhood, whereas Latin-based words fill in the lexical space across adolescence and into early adulthood. Furthermore, L2 speakers appear to acquire English via more advanced Latin-based vocabulary relative to native speakers. These results carry implications for theories of word recognition and the processing of lexical items in populations that come from linguistically diverse backgrounds.

LOPO: a location privacy preserving path optimization scheme for spatial crowdsourcing

While spatial crowdsourcing has become a popular paradigm for spatio-temporal data collection, location privacy has raised increasing concerns among the participants of spatial crowdsourcing projects in recent years. The question of how to implement a spatial crowdsourcing project at minimal cost while preserving location privacy, is the major issue that most existing works have investigated. In this paper, we propose a novel privacy-preserving method for spatial crowdsourcing that combines location obfuscation and path optimization in order to provide enhanced privacy preservation at a minimal cost. We apply geo-indistinguishability and exponential mechanism to achieve an enhanced privacy guarantee. Moreover, because a higher privacy level consistently leads to extra distance cost, we therefore present a path optimization algorithm that reduces the total distance of a spatial crowdsourcing project. The experimental results demonstrate that the proposed method outperforms the traditional methods in terms of privacy level and performance costs.

Motivation to engage in crowdsourcing: Towards the synthetic psychological–sociological model

Abstract This article is aimed at analysis of user participation in web-based crowdsourcing projects in the digital humanities (DH) field, with a focus on what motivates these volunteers.1 The first aim of the article is a critical analysis of models of motivators for involvement offered to date. The analysis is based on a review of DH crowdsourcing literature, as a result of which there is an indication of shortcomings of the psychological data-driven approach that has dominated thus far. The second aim of the article is to offer a new model that synthesizes the psychological-motivation approach with a sociological one. Applying Pierre Bourdieu’s Theory of Capital, the motivation model created by the psychological self-determination theory (SDT) is supplemented with capital dimensions and specific types of capital. The new model is empirically tested, utilizing specific data collected in the course of a crowdsourcing project, specifically, volunteers’ online survey. The conclusion states that the model synthesized using the psychological and sociological approach preserves the main SDT category scale (intrinsic–extrinsic), at the same time, the sociological capital categories implemented therein permit for making more concrete the psychological scale’s ‘intermediate phase’ (internalized extrinsic motivations) that had been amorphous up to that point, rendering the motivation model more coherent and readily applied.

Seasonality of mood and affect in a large general population sample.

Mood and behaviour are thought to be under considerable influence of the seasons, but evidence is not unequivocal. The purpose of this study was to investigate whether mood and affect are related to the seasons, and what is the role of neuroticism in this association. In a national internet-based crowdsourcing project in the Dutch general population, individuals were invited to assess themselves on several domains of mental health. ANCOVA was used to test for differences between the seasons in mean scores on the Positive and Negative Affect Schedule (PANAS) and Quick Inventory of Depressive Symptomatology (QIDS). Within-subject seasonal differences were tested as well, in a subgroup that completed the PANAS twice. The role of neuroticism as a potential moderator of seasonality was examined. Participants (n = 5,282) scored significantly higher on positive affect (PANAS) and lower on depressive symptoms (QIDS) in spring compared to summer, autumn and winter. They also scored significantly lower on negative affect in spring compared to autumn. Effect sizes were small or very small. Neuroticism moderated the effect of the seasons, with only participants higher on neuroticism showing seasonality. There was no within-subject seasonal effect for participants who completed the questionnaires twice (n = 503), nor was neuroticism a significant moderator of this within-subjects effect. The findings of this study in a general population sample participating in an online crowdsourcing study do not support the widespread belief that seasons influence mood to a great extent. For, as far as the seasons did influence mood, this only applied to highly neurotic participants and not to low-neurotic participants. The underlying mechanism of cognitive attribution may explain the perceived relation between seasonality and neuroticism.

Clustering Crowdsourced Test Reports of Mobile Applications Using Image Understanding

Crowdsourced testing has been widely used to improve software quality as it can detect various bugs and simulate real usage scenarios. Crowdsourced workers perform tasks on crowdsourcing platforms and present their experiences as test reports, which naturally generates an overwhelming number of test reports. Therefore, inspecting these reports becomes a time-consuming yet inevitable task. In recent years, many text-based prioritization and clustering techniques have been proposed to address this challenge. However, in mobile testing, test reports often consist of only short test descriptions but rich screenshots. Compared with the uncertainty of textual information, well-defined screenshots can often adequately express the mobile application's activity views. In this paper, by employing image-understanding techniques, we propose an approach for clustering crowdsourced test reports of mobile applications based on both textual and image features to assist the inspection procedure. We employ Spatial Pyramid Matching (SPM) to measure the similarity of the screenshots and use the natural-language-processing techniques to compute the textual distance of test reports. To validate our approach, we conducted an experiment on 6 industrial crowdsourced projects that contain more than 1600 test reports and 1400 screenshots. The results show that our approach is capable of outperforming the baselines by up to 37% regarding the APFD metric. Further, we analyze the parameter sensitivity of our approach and discuss the settings for different application scenarios.

Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks

After a hurricane, damage assessment is critical to emergency managers for efficient response and resource allocation. One way to gauge the damage extent is to quantify the number of flooded/damaged buildings, which is traditionally done by ground survey. This process can be labor-intensive and time-consuming. In this paper, we propose to improve the efficiency of building damage assessment by applying image classification algorithms to post-hurricane satellite imagery. At the known building coordinates (available from public data), we extract square-sized images from the satellite imagery to create training, validation, and test datasets. Each square-sized image contains a building to be classified as either 'Flooded/Damaged' (labeled by volunteers in a crowd-sourcing project) or 'Undamaged'. We design and train a convolutional neural network from scratch and compare it with an existing neural network used widely for common object classification. We demonstrate the promise of our damage annotation model (over 97% accuracy) in the case study of building damage assessment in the Greater Houston area affected by 2017 Hurricane Harvey.