The Botization of Science? Large-scale study of the presence and impact of Twitter bots in science dissemination

Twitter bots are a controversial element of the platform, and their negative impact is well known. In the field of scientific communication, they have been perceived in a more positive light, and the accounts that serve as feeds alerting about scientific publications are quite common. However, despite being aware of the presence of bots in the dissemination of science, no large-scale estimations have been made nor has it been evaluated if they can truly interfere with altmetrics. Analyzing a dataset of 3,744,231 papers published between 2017 and 2021 and their associated 51,230,936 Twitter mentions, our goal was to determine the volume of publications mentioned by bots and whether they skew altmetrics indicators. Using the BotometerLite API, we categorized Twitter accounts based on their likelihood of being bots. The results showed that 11,073 accounts (0.23% of total users) exhibited automated behavior, contributing to 4.72% of all mentions. A significant bias was observed in the activity of bots. Their presence was particularly pronounced in disciplines such as Mathematics, Physics, and Space Sciences, with some specialties even exceeding 70% of the tweets. However, these are extreme cases, and the impact of this activity on altmetrics varies by speciality, with minimal influence in Arts & Humanities and Social Sciences. This research emphasizes the importance of distinguishing between specialties and disciplines when using Twitter as an altmetric

Issues in the Interpretation of “Altmetrics” Digital Traces: A Review

Researchers leave traces of their behavior during many stages of their research process. Parts of this process were formerly invisible. With scholarship moving online, we can now access various types of altmetrics digital traces such as reading, organizing, sharing, and discussing scientific papers, thus develop a more holistic story about researchers and their work. However, a lack of in-depth interpretation of altmetrics digital traces is observed. Therefore, this paper focuses on reviewing some of the existing altmetrics research, with a particular emphasis on the issues that need to be taken into consideration in the interpretation of altmetrics digital traces. Taking a preliminary step toward a guideline for more in-depth analysis of digital traces of scholarly acts, this review aims to bring attention to these issues to avoid misuse of altmetrics indicators

Invasion genetics and development of rapid diagnostics of insect pests on traded plants

Background: Global trade of plant products is a major driving force for the unintended spread of economically harmful insect pests. This PhD thesis aimed at (i) developing and implementing molecular tools for the on-site identification of invasive insect pests at points of entry (POEs) for plant import products as a prevention measure; and (ii) investigating the invasion history of the mosaic leafhopper Orientus ishidae, a potential vector of grapevine Flavescence dorée phytoplasma. Methods: To achieve the first goal, loop-mediated isothermal amplification (LAMP)-based genetic assays for the rapid on-site identification of Bemisia tabaci, Thrips palmi and several invasive fruit flies of the genera Bactrocera and Zeugodacus were developed. Using publicly available DNA sequences, LAMP primers were designed to specifically target a fragment of the mitochondrial cytochrome c oxidase subunit 1 gene. To address the second goal of this PhD thesis, the invasion genetics of O. ishidae was studied, an invasive insect species that spread from its native range from in East Asia to North America in the first half of the 20th century and only recently colonised Europe. Possible source populations and invasion pathways were investigated by assessing the genetic structure of 41 O. ishidae populations from Asia, Europe, and North America based on a mitochondrial marker and 641 single nucleotide polymorphisms (SNPs) generated by double digest restriction-site associated DNA (ddRAD) sequencing. Results: Validation performed under laboratory and on-site conditions demonstrated the robustness and reliability of the developed LAMP identification assays. Analysing 319 insect specimens, the overall diagnostic test efficiency was 98% and the overall diagnostic test specificity was 100%. The small number of false-negative results (2%) originated either from previously unknown biotypes, not included in the initial primer design, or from handling errors during LAMP preparation. The results from the molecular genetic analyses of O. ishidae revealed a clear genetic separation between a native population from Asia and the non-native populations from Europe and North America. Among the non-native populations, only faint signals of spatial genetic structuring were found. However, when comparing non-native populations from Europe and North America, elevated levels of admixture of genetically distant mitochondrial haplotypes were observed for European populations. Conclusion: Characterised by high analysis speed (<1 h) and simplicity in use (only 1 pipetting step), the validated LAMP assays were found to be suitable identification tools for on-site application by plant health inspectors. Since completion of the validation phase, the developed identification assays are routinely deployed in the phytosanitary import control process of Switzerland. The considerable genetic separation between native and non-native populations of O. ishidae together with the strikingly high genetic similarity of European and North American populations suggest an invasion scenario in which North American populations served as source for the European invasion. A slightly reduced genetic structure combined with increased admixture of genetically distant mitochondrial haplotypes furthermore indicate that the European colonisation history was shaped by multiple introductions from North America, complemented by frequent intra-European gene flow. Taken together, it is hypothesised that the overall genetic complexity of non-native populations was strongly driven by frequent international trade of plants infested by O. ishidae

UNDERSTANDING THE SCHOLARLY COMMUNICATION PROCESS THROUGH DIGITAL TRACES: A STUDY OF TWITTER

Through the lens of the exploratory framework of Digital Trace of Scholarly Acts (DTSA), this dissertation study explored researchers’ activities around scholarly articles on Twitter. Using a mixed-methods design, this study analyzed data collected from a large-scale survey and twenty interviews with researchers on Twitter. The Critical Incident Technique was used as part of the interview study to learn about the full stories behind researchers’ sharing of scholarly articles on Twitter. There were variations in the researcher’s sentiment of opinions on articles they tweeted, retweeted, replied, and liked, based on their demographics. Despite a general positive tendency, researchers’ Twitter activities were associated with different sentiment due to their different perceptions of these activities. Variations were also found in how sharing scholarly articles on Twitter fit into researchers’ scholarly acts workflow with no monolithic pattern. This study contributed to a better understanding of the digital traces left by researchers on Twitter by providing richer descriptions and narratives of their activities. Researchers shared scholarly articles on Twitter for a variety of motivations: networking, promoting, disseminating, commenting, communicating with intended users, acknowledgment, and saving for later reference. The findings particularly shed light on the role of Twitter in communicating research and network building. Investigating the impact of the articles on the researchers led to a better understanding of what types of articles had a higher premium of sharing by researchers on Twitter. Evidence was found to support both the normative theory and the constructivist theory – the categories of impact included connecting, informing, practice-changing, beyond research, and potential impact. However, more than half of the shared articles examined had no impact on the researchers’ own work, indicating that Twitter metrics, even solely based on researchers’ Twitter activities, should not be used as an evaluative metric of the articles shared.Doctor of Philosoph