Working the crowd for forensic research: A review of contributor motivation and recruitment strategies used in crowdsourcing and crowdfunding for scientific research

Understanding crowdsourcing in science

Over the past 16 years, the concept of crowdsourcing has rapidly gained traction across many research fields. While related debates focused mainly on its importance for business, the public and non-governmental sectors, its relevance for generating scientific knowledge is increasingly emphasized. This rising interest remains in contradiction with its feeble recognition, and excessive simplifications reducing crowdsourcing in science to citizen science. Conceptual clarity and a coherent framework would help integrate the various research streams. The aim of this paper is to extend reflection on crowdsourcing in science by analyzing the characteristics of the phenomenon. We synthesize a consensual definition from the literature, and structure key characteristics into a coherent framework, useful in guiding further research. We use a systematic literature review procedure to generate a pool of 42 definitions from a comprehensive set of 62 articles spanning different literatures, including: business and economics, education, psychology, biology, and communication studies. We follow a mixed-method approach that combines bibliometric and frequency analyses with deductive coding and thematic analysis. Based on triangulated results we develop an integrative definition: crowdsourcing in science is a collaborative online process through which scientists involve a group of self-selected individuals of varying, diverse knowledge and skills, via an open call to the Internet and/or online platforms, to undertake a specified research task or set of tasks. We also provide a conceptual framework that covers four key characteristics: initiator, crowd, process, and technology.

Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?

Background

Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest.

Objective

This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster.

Methods

This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking “How to faster end the COVID-19 pandemic?” and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes – personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users.

Results

The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results.

Conclusions

Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance.

Towards a typology development of crowdsourcing in science

Crowdsourcing in science as collaborative online process through which non-professional and/or professional scientists incorporate a group of individuals of varying, diversity knowledge and skills, via an open call to the Internet and/or online platforms, to undertaking of a task in science, is an important strategy to support scientific research that has gained attention in academia and practitioners. While research efforts to date have focused on the benefits of crowdsourcing in science, its typology has yet to mature. Typologies are important in describing complex, multidisciplinary organisational forms such as crowdsourcing in science. The main purpose of this article is to identify and provide a typology of crowdsourcing in science. Based on the thematic analysis of publications collected in a systematic manner and focused group interviews, 12 types of crowdsourcing in science are identified. The proposed crowdsourcing in science typology matrix may be a starting point for future research and decision-making by practitioners regarding the choice of a specific type of crowdsourcing in science.