scholarly journals Social Media and citizen science provide valuable data for behavioural ecology research: Are cuttlefish using pursuit-deterrent signals during hunting?

2019 ◽  
Author(s):  
Dražen Gordon ◽  
Philip Pugh ◽  
Gavan M Cooke
Keyword(s):  
Social Media ◽  
Citizen Science ◽  
Prey Type ◽  
Behavioural Ecology ◽  
Data Sets ◽  
Marine Animals ◽  
Sepia Pharaonis ◽  
Hunting Strategies ◽  
Sepia Apama ◽  
Permutation Analysis

AbstractObtaining robust, analysable data sets from wild marine animals is fraught with difficulties, dangers, expense, often without success. Scientists are becoming increasingly reliant on citizen scientists to help fill in gaps where they exist, especially in the area of biodiversity. Here, uniquely, we use social media and citizen science videos to investigate the behavioural ecology of hunting in five cuttlefish species – Metasepia pfefferi (N = 24), Sepia apama (N = 13), Sepia latimanus (N = 8), Sepia officinalis (N = 17), and Sepia pharaonis (N = 23). We find that hunting strategies and prey type differ between species as do the types of behaviours used by the five species studied here. We also use kinematic permutation analysis to elucidate chains of behaviours, finding that cuttlefish significantly use a mixture of predator behaviours but also prey-like behaviours, such as warning signals and possibly even a ‘pursuit-deterrent signal’ during the final moments of hunting. We also show and discuss significant intraspecific differences.

scholarly journals Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Comprehensive Evaluation ◽  
Classification Problem ◽  
Data Sets ◽  
Word Embeddings ◽  
Data Set ◽  
Lower Accuracy ◽  
Health Related ◽  
The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

scholarly journals Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

2021 ◽  
pp. 089443932110122
Author(s):  
Dennis Assenmacher ◽  
Derek Weber ◽  
Mike Preuss ◽  
André Calero Valdez ◽  
Alison Bradshaw ◽  
...  
Keyword(s):  
Social Media ◽  
Data Sharing ◽  
Algorithm Design ◽  
Computational Social Science ◽  
Evaluation Framework ◽  
Social Media Analytics ◽  
Data Sets ◽  
The Public ◽  
Research Areas ◽  
Media Data

Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.

The Patient in Patient Safety: Contemporary Issues, From COVID-19 to Citizen Science

2021 ◽  
Vol 10 (1) ◽  
pp. 301-303
Author(s):  
Elizabeth Lerner Papautsky ◽  
Richard J. Holden ◽  
Rupa S. Valdez ◽  
Jordan Hill ◽  
Janetta Brown
Keyword(s):  
Social Media ◽  
Patient Safety ◽  
Citizen Science ◽  
Human Subjects ◽  
Lessons Learned ◽  
Human Subjects Research ◽  
Research Strategies ◽  
Face To Face

In the 4th panel on the topic of The Patient in Patient Safety, we highlighted topics of current relevance and facilitated a reflection session. The objective was to highlight the ways in which the COVID-19 pandemic has impacted patient ergonomics research and work, with particular focus on safety. After a topic overview, panelists presented their work on overcoming challenges to human subjects research created by the suspension of face-to-face activities during the COVID-19 pandemic. A facilitated reflection and brainstorming session using Miro followed. We used questions to elicit examples of patient and caregiver roles in safety during the pandemic and research strategies and challenges. These questions were also distributed on social media prior to the event. The panel served as an opportunity to share lessons learned.

scholarly journals Citizen science via social media revealed conditions of symbiosis between a marine gastropod and an epibiotic alga

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Osamu Kagawa ◽  
◽  
Shota Uchida ◽  
Daishi Yamazaki ◽  
Yumiko Osawa ◽  
...  
Keyword(s):  
Social Media ◽  
Heat Stress ◽  
Environmental Factors ◽  
Citizen Science ◽  
Bayesian Model ◽  
Symbiotic Relationship ◽  
Hierarchical Bayesian Model ◽  
Symbiotic Interaction ◽  
Intertidal Gastropod ◽  
Substrate Size

AbstractEnvironmental factors promote symbiosis, but its mechanism is not yet well understood. The alga Pseudocladophora conchopheria grows only on the shell of an intertidal gastropod Lunella correensis, and these species have a close symbiotic relationship which the alga reduces heat stress of the gastropod. In collaboration with general public, we investigated how environmental conditions alter the symbiotic interaction between the alga and the gastropod. Information about the habitats of each gastropod and images of shells was obtained from the Japanese and Korean coasts via social media. We constructed the hierarchical Bayesian model using the data. The results indicated that the proportion of shell area covered by P. conchopheria increased as the substrate size utilized by the gastropod increased. Meanwhile, temperature did not affect the proportion of P. conchopheria on the shell. These suggested that the alga provides no benefits for the gastropod on small substrates because gastropod can reduce the heat stress by diving into the small sediment. Further, the gastropod’s cost incurred by growing the alga on the shell seems to be low as the algae can grow even in cooler places where no benefits of heat resistance for gastropods. Different environments can yield variable conditions in symbiosis.

Building Data Sets for Rainforest Deforestation Detection Through a Citizen Science Project

2020 ◽  
pp. 1-5
Author(s):  
Fernanda Beatriz Jordan Rojas Dallaqua ◽  
Fabio Augusto Faria ◽  
Alvaro Luiz Fazenda
Keyword(s):  
Citizen Science ◽  
Data Sets ◽  
Science Project ◽  
Citizen Science Project

scholarly journals A behavioural ecology approach to understand volunteer surveying for citizen science datasets

2012 ◽  
Vol 112 (4) ◽  
pp. 313-325 ◽  
Author(s):  
Ayesha I. T. Tulloch ◽  
Judit K. Szabo
Keyword(s):  
Citizen Science ◽  
Behavioural Ecology

Biotic and Abiotic Controls on the Phanerozoic History of Marine Animal Biodiversity

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Andrew M. Bush ◽  
Jonathan L. Payne
Keyword(s):  
Biotic Interactions ◽  
Annual Review ◽  
Publication Date ◽  
Data Sets ◽  
Marine Animal ◽  
Marine Animals ◽  
Marine Habitat ◽  
Positive Feedbacks ◽  
Abiotic Controls ◽  
Time Changes

During the past 541 million years, marine animals underwent three intervals of diversification (early Cambrian, Ordovician, Cretaceous–Cenozoic) separated by nondirectional fluctuation, suggesting diversity-dependent dynamics with the equilibrium diversity shifting through time. Changes in factors such as shallow-marine habitat area and climate appear to have modulated the nondirectional fluctuations. Directional increases in diversity are best explained by evolutionary innovations in marine animals and primary producers coupled with stepwise increases in the availability of food and oxygen. Increasing intensity of biotic interactions such as predation and disturbance may have led to positive feedbacks on diversification as ecosystems became more complex. Important areas for further research include improving the geographic coverage and temporal resolution of paleontological data sets, as well as deepening our understanding of Earth system evolution and the physiological and ecological traits that modulated organismal responses to environmental change. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 52 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter

2019 ◽  
Vol 43 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Ahmed Al-Rawi ◽  
Jacob Groshek ◽  
Li Zhang
Keyword(s):  
Social Media ◽  
Data Sets ◽  
Fake News ◽  
Content Type ◽  
Mainstream Media ◽  
News Discourse ◽  
Twitter Data ◽  
News Organizations ◽  
Twitter Users ◽  
One Year

PurposeThe purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users.Design/methodology/approachTweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed.FindingsThe majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways.Research limitations/implicationsThe research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is.Originality/valueThis paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.

scholarly journals Citizen Participation in Responding to Natural Disasters Through Twitter Messages

2020 ◽  
Vol 5 (2) ◽  
pp. 123
Author(s):  
Rizky Pamuji ◽  
Ismiarta Aknuranda ◽  
Fatwa Ramdani
Keyword(s):  
Social Media ◽  
Natural Disasters ◽  
Citizen Science ◽  
Citizen Participation ◽  
Disaster Relief ◽  
Local Communities ◽  
Citizen Involvement ◽  
The Government

Citizen participation in collect and distribute information increase the role of the citizen involvement in local issues and increasing the benefits of society for the government and the environment. The contribution of citizens can be useful in helping to deal with environment problems and assist certain parties in meeting data needs, this is commonly referred to as citizen science. In its development, citizen science involvement in providing information began to involve social media as a platform for sharing information. In this study we try to explore citizen science of Indonesia, we conduct case study exploring how citizen in Indonesia used social media such as Twitter in response to one of the country’s worst disaster in 2018 namely Lombok Earthquake. By analyzing these user generate message we may know what the response of Indonesian citizen during event and understand more about citizen science in Indonesia through social media including its role and contribution. The information also may assist local communities in obtaining up-to-date information, providing assistance according to needs of the populace and use to manage and plan disaster relief both during and after the event.

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