Do citizen scientists use different technologies depending on their age in CS activities?

In this interview, we talk to two professionals who have each worked in different research fields which have utilized citizen scientists as part of their profession and research.

Volunteers in citizen science (CS) have different kinds of motivations for participation, ranging from e.g. topic interest, supporting science to personal recognition. Information regarding the existence and characteristics of motivation profile groups of volunteers remains unclear.

Citizen science (CS) projects encompass a variety of different disciplines (e.g. health, biology, education). However, it is not clear whether volunteers’ working i.e. professional discipline is related to the discipline of their selected project. 

Citizen science engages adults of all age groups. According to participants, which are technologies they use to participate in CS activities? What are the differences between different age groups and the technologies they use?

Since November 2019 the international research project CS Track has been combining traditional social-science methods with web-based and computational analytics in order to systematically survey the field of Citizen Science.

Since November 2019 the international research project CS Track has been combining traditional social-science methods with web-based and computational analytics in order to systematically survey the field of Citizen Science.

Since November 2019 the international research project CS Track has been combining traditional social-science methods with web-based and computational analytics in order to systematically survey the field of Citizen Science.

We are delighted to announce that the article entitled “Inclusion and exclusion in citizen science: A matter of context” written by Michael Strähle and Christine Urban has been published in the conference proceedings of the STS Conference Graz 2022 that took place from 2-4 May 2022.

Main aim of the study This work presents opportunities, achievements, and future challenges in using computational analytics to better understand the connection between CS and the SDGs. The work in its status does not fully cover SDGs in CS, but it evaluates and shows the potential of the text-classification

The study aimed at assessing the pandemic’s impact on online CS participation and capturing CS project coordinators’ experience of the pandemic and their actions in managing the pandemic’s effects. 

Collect data on some project characteristics which cannot be answered by visiting project websites.

This study aims at understanding how the alignment between the motivational factors of CS participants and the recruitment speech used in the projects’ description is, by performing quantitative triangulation of data collected through a survey about 12 motivational factors for participating in a CS project, and the manual analysis

The study aim is to investigate how a combination of methods (such as data analysis, computational or quantitative methods) could be applied to gather CS projects information to support teacher’s practice and inspire them. 

In this case study we intended to reflect on how the online data about CS is shared and communicated in the websites, how could this data be extracted massively and stored in a central database to, later be analysed with different purposes. One of its, studied in this article,

Project descriptions are a central element of a Citizen Science project’s online presence and thus play a key role in recruiting volunteers. Very often, they are the first point of contact between a project and prospective participants. As such, they need to be reader-friendly and accessible, spark interest, contain