We are pleased to announce publication of the first issue of JCOM for 2016.
SPECIAL ISSUE: CITIZEN SCIENCE, PART I
We are delighted to publish the first in a two part series exploring Citizen Science. Following a call for papers, Bruce Lewenstein and Emma Weitkamp received 37 manuscripts. Following review, it was clear that we would need two issues to accommodate the many worthy submissions. This newsletter introduces the essays and research papers that form part one of the Special Issue. April will see the publication of part two, and the final papers accepted through the call. We thank all the authors submitting manuscripts and the many reviewers contributing their time to peer review papers.
Can we understand citizen science?
Bruce V. Lewenstein
Citizen science is one of the most dramatic developments in science communication in the last generation. But analyses of citizen science, of what it means for science and especially for science communication, have just begun to appear. Articles in this first of two special issues of JCOM address three intertwined concerns in this emerging field: The motivation of citizen science participants, the relationship of citizen science with education, and the implications of participation for creation of democratic engagement in science-linked issues. Ultimately these articles contribute to answering the core question: What does citizen science mean?
ARTICLES AND ESSAYS
Tony Bellovary passed along the following, although I’m sure many of you have seen this already:
Google Flu Trends uses aggregated Google search data to track flu activity up to two weeks faster than traditional flu surveillance systems.
Each week, millions of users around the world search for online health information. As you might expect, there are more flu-related searches during flu season, more allergy-related searches during allergy season, and more sunburn-related searches during the summer. You can explore all of these phenomena using Google Trends. But can search query trends provide an accurate, reliable model of real-world phenomena? We have found a close relationship between how many people search for flu-related topics and how many people actually have flu symptoms. For full text, visit: http://www.google.org/about/flutrends/how.html
Google can in fact whip up a list of people who search for particular terms (identified by IP address and/or cookie value). Google has admitted this. So I’m not sure their privacy statement about not being able to identify people searching for keywords relating to flu holds. Just imagine for a moment that a person searches for “symptoms of AIDS” or “alcoholism signs”. Search terms and history reveal a lot of personal information and if linked to a particular user, there could be adverse consequences for employment, insurance or travel.
The Electronic Privacy Information Center (EPIC) shares similar concerns. EPIC sent a letter to Google’s CEO urging Google to be transparent and reveal the algorithm on which Flu Trends data is based and disclose exactly how Google protects privacy. …
Citing the paper Trail Re-Identification: Learning Who You Are From Where You Have Been, Kim comments that “re-identification” algorithms used to link IP addresses to individuals can be extended to track co-locations of people. Kim asks, “could Google Flu Trends, coupled with Google Health,” lead to “insurance companies identifying areas as prone to certain diseases and denying health insurance”?
For full text of this post, visit: http://thinkingshift.wordpress.com/2008/11/20/google-tracks-flu/