scholarly journals Automatic detection of influential actors in disinformation networks

2021 ◽  
Vol 118 (4) ◽  
pp. e2011216118
Author(s):  
Steven T. Smith ◽  
Edward K. Kao ◽  
Erika D. Mackin ◽  
Danelle C. Shah ◽  
Olga Simek ◽  
...  
Keyword(s):  
Language Processing ◽  
Presidential Elections ◽  
High Impact ◽  
Network Centrality ◽  
Investigative Journalism ◽  
Graph Analytics ◽  
Network Communities ◽  
Automate Detection ◽  
New Challenges ◽  
The Impact

The weaponization of digital communications and social media to conduct disinformation campaigns at immense scale, speed, and reach presents new challenges to identify and counter hostile influence operations (IOs). This paper presents an end-to-end framework to automate detection of disinformation narratives, networks, and influential actors. The framework integrates natural language processing, machine learning, graph analytics, and a network causal inference approach to quantify the impact of individual actors in spreading IO narratives. We demonstrate its capability on real-world hostile IO campaigns with Twitter datasets collected during the 2017 French presidential elections and known IO accounts disclosed by Twitter over a broad range of IO campaigns (May 2007 to February 2020), over 50,000 accounts, 17 countries, and different account types including both trolls and bots. Our system detects IO accounts with 96% precision, 79% recall, and 96% area-under-the precision-recall (P-R) curve; maps out salient network communities; and discovers high-impact accounts that escape the lens of traditional impact statistics based on activity counts and network centrality. Results are corroborated with independent sources of known IO accounts from US Congressional reports, investigative journalism, and IO datasets provided by Twitter.

Larvae of the blow fly Caiusa testacea (Diptera: Calliphoridae) as egg predators of Polypedates cruciger Blyth, 1852 (Amphibia: Anura: Rhacophoridae)

2020 ◽  
Vol 12 (17) ◽  
pp. 17374-17379
Author(s):  
W.G.D. Chathuranga ◽  
K. Kariyawasam ◽  
Anslem De Silva ◽  
W.A.Priyanka P. De Silva
Keyword(s):  
Sri Lanka ◽  
High Impact ◽  
Tree Frog ◽  
Blow Fly ◽  
Breeding Habitats ◽  
The Family ◽  
Water Container ◽  
The Common ◽  
Natural Breeding ◽  
The Impact

We investigated the impact of dipteran predators on eggs in foam nests of the Common Hour-glass Tree Frog Polypedates cruciger Blyth, 1852 (Anura: Rhacophoridae) in central Sri Lanka.  Foam nests (n=24) of P. cruciger were examined at their natural breeding habitats and infected (n=8) and uninfected spawns (n=16) were identified.  Emerging tadpoles were collected in a water container hung under each spawn and the average number of tadpoles (N) hatched from infected spawns (N=0) was compared with that of uninfected spawns (N=354 ± 67).  Three severely infected spawns were brought to the laboratory and the fly larvae were reared until they metamorphosed to adults.  Morphological and molecular identification of the flies confirmed them as belonging to Caiusa testacea Senior-White, 1923 of the family Calliphoridae.  The infected spawns were completely destroyed and an estimated average of 400 P. cruciger eggs per spawn were lost.  The results revealed a high impact of Caiusa testacea on egg and embryo mortality of P. cruciger.

Freedom of Expression versus Privacy and the Right to Reputation

2017 ◽  
Author(s):  
Dirk Voorhoof
Keyword(s):  
Public Interest ◽  
Freedom Of Expression ◽  
Media Freedom ◽  
Investigative Journalism ◽  
The Public ◽  
The Right Of Privacy ◽  
The One ◽  
Grand Chamber ◽  
The Right ◽  
The Impact

The normative perspective of this chapter is how to guarantee respect for the fundamental values of freedom of expression and journalistic reporting on matters of public interest in cases where a (public) person claims protection of his or her right to reputation. First it explains why there is an increasing number and expanding potential of conflicts between the right to freedom of expression and media freedom (Article 10 ECHR), on the one hand, and the right of privacy and the right to protection of reputation (Article 8 ECHR), on the other. In addressing and analysing the European Court’s balancing approach in this domain, the characteristics and the impact of the seminal 2012 Grand Chamber judgment in Axel Springer AG v. Germany (no. 1) are identified and explained. On the basis of the analysis of the Court’s subsequent jurisprudence in defamation cases it evaluates whether this case law preserves the public watchdog-function of media, investigative journalism and NGOs reporting on matters of public interest, but tarnishing the reputation of public figures.

PODC 2020 Review

2021 ◽  
Vol 51 (4) ◽  
pp. 75-81
Author(s):  
Ahad Mirza Baig ◽  
Alkida Balliu ◽  
Peter Davies ◽  
Michal Dory
Keyword(s):  
Machine Learning ◽  
Distributed Computing ◽  
Keynote Speaker ◽  
Lively Discussion ◽  
Theoretical Understanding ◽  
New Directions ◽  
New Ideas ◽  
New Challenges ◽  
The Impact ◽  
Distributed Machine Learning

Rachid Guerraoui was the rst keynote speaker, and he got things o to a great start by discussing the broad relevance of the research done in our community relative to both industry and academia. He rst argued that, in some sense, the fact that distributed computing is so pervasive nowadays could end up sti ing progress in our community by inducing people to work on marginal problems, and becoming isolated. His rst suggestion was to try to understand and incorporate new ideas coming from applied elds into our research, and argued that this has been historically very successful. He illustrated this point via the distributed payment problem, which appears in the context of blockchains, in particular Bitcoin, but then turned out to be very theoretically interesting; furthermore, the theoretical understanding of the problem inspired new practical protocols. He then went further to discuss new directions in distributed computing, such as the COVID tracing problem, and new challenges in Byzantine-resilient distributed machine learning. Another source of innovation Rachid suggested was hardware innovations, which he illustrated with work studying the impact of RDMA-based primitives on fundamental problems in distributed computing. The talk concluded with a very lively discussion.

scholarly journals A Natural Language Processing Approach to Measuring Treatment Adherence and Consistency Using Semantic Similarity

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842110286
Author(s):  
Kylie L. Anglin ◽  
Vivian C. Wong ◽  
Arielle Boguslav
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Intervention Implementation ◽  
Proof Of Concept ◽  
Coaching Intervention ◽  
Processing Techniques ◽  
Teacher Coaching ◽  
The Impact

Though there is widespread recognition of the importance of implementation research, evaluators often face intense logistical, budgetary, and methodological challenges in their efforts to assess intervention implementation in the field. This article proposes a set of natural language processing techniques called semantic similarity as an innovative and scalable method of measuring implementation constructs. Semantic similarity methods are an automated approach to quantifying the similarity between texts. By applying semantic similarity to transcripts of intervention sessions, researchers can use the method to determine whether an intervention was delivered with adherence to a structured protocol, and the extent to which an intervention was replicated with consistency across sessions, sites, and studies. This article provides an overview of semantic similarity methods, describes their application within the context of educational evaluations, and provides a proof of concept using an experimental study of the impact of a standardized teacher coaching intervention.

scholarly journals Evaluating Cultural Impact in Discursive Space through Digital Footprints

2021 ◽  
Vol 13 (7) ◽  
pp. 4043 ◽  
Author(s):  
Jesús López Baeza ◽  
Jens Bley ◽  
Kay Hartkopf ◽  
Martin Niggemann ◽  
James Arias ◽  
...  
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Social Activity ◽  
Test Site ◽  
Cultural Discourse ◽  
Discursive Space ◽  
Topic Identification ◽  
Small Test ◽  
The Impact ◽  
The City

The research presented in this paper describes an evaluation of the impact of spatial interventions in public spaces, measured by social media data. This contribution aims at observing the way a spatial intervention in an urban location can affect what people talk about on social media. The test site for our research is Domplatz in the center of Hamburg, Germany. In recent years, several actions have taken place there, intending to attract social activity and spotlight the square as a landmark of cultural discourse in the city of Hamburg. To evaluate the impact of this strategy, textual data from the social networks Twitter and Instagram (i.e., tweets and image captions) are collected and analyzed using Natural Language Processing intelligence. These analyses identify and track the cultural topic or “people talking about culture” in the city of Hamburg. We observe the evolution of the cultural topic, and its potential correspondence in levels of activity, with certain intervention actions carried out in Domplatz. Two analytic methods of topic clustering and tracking are tested. The results show a successful topic identification and tracking with both methods, the second one being more accurate. This means that it is possible to isolate and observe the evolution of the city’s cultural discourse using NLP. However, it is shown that the effects of spatial interventions in our small test square have a limited local scale, rather than a city-wide relevance.

The Impact of COVID-19: Democracy in the Time of a Pandemic

Social Change ◽  
2021 ◽  
Vol 51 (4) ◽  
pp. 475-482
Author(s):  
Zoya Hasan
Keyword(s):  
Social Sciences ◽  
Human Rights ◽  
Social Development ◽  
Health Crisis ◽  
Domain Experts ◽  
Sharp Focus ◽  
The World ◽  
Democratic Rights ◽  
New Challenges ◽  
The Impact

The recent spread of the delta variant of the COVID-19 pandemic in many countries, though uneven, has once again set alarm bells ringing throughout the world. Nearly two years have passed since the onset of this pandemic: vaccines have been developed and vaccination is underway, but the end of the campaign against the pandemic is nowhere in sight. This drive has merely attempted to adjust and readjust, with or without success, to the various fresh challenges that have kept emerging from time to time. The pandemic’s persistence and its handling by the governments both have had implications for citizens’/peoples’ rights as well as for the systems which were in place before the pandemic. In this symposium domain experts investigate, with a sharp focus on India, the interface between the COVID-19 pandemic and democracy, health, education and social sciences. These contributions are notable for their nuanced and insightful examination of the impact of the pandemic on crucial social development issues with special attention to the exacerbated plight of society’s marginalised sections. In India, as in several other countries, the COVID-19 pandemic has affected democracy. The health crisis came at a moment when India was already experiencing democratic backsliding. The pandemic came in handy in imposing greater restrictions on democratic rights, public discussion and political opposition. This note provides an analysis and commentary on how the government’s response to the COVID-19 pandemic impacted governance, at times undermining human rights and democratic processes, and posing a range of new challenges to democracy.

Leveraging Twitter Using Artificial Intelligence to Explore Mental Health Insights in the UK During the COVID-19 Pandemic (Preprint)

2021 ◽  
Author(s):  
Christopher Marshall ◽  
Kate Lanyi ◽  
Rhiannon Green ◽  
Georgie Wilkins ◽  
Fiona Pearson ◽  
...  
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Language Processing ◽  
Mental Health Problems ◽  
Well Being ◽  
Research Activity ◽  
Health Crisis ◽  
Key Topics ◽  
The Uk ◽  
The Impact

BACKGROUND There is increasing need to explore the value of soft-intelligence, leveraged using the latest artificial intelligence (AI) and natural language processing (NLP) techniques, as a source of analysed evidence to support public health research activity and decision-making. OBJECTIVE The aim of this study was to further explore the value of soft-intelligence analysed using AI through a case study, which examined a large collection of UK tweets relating to mental health during the COVID-19 pandemic. METHODS A search strategy comprising a list of terms related to mental health, COVID-19, and lockdown restrictions was developed to prospectively collate relevant tweets via Twitter’s advanced search application programming interface over a 24-week period. We deployed a specialist NLP platform to explore tweet frequency and sentiment across the UK and identify key topics of discussion. A series of keyword filters were used to clean the initial data retrieved and also set up to track specific mental health problems. Qualitative document analysis was carried out to further explore and expand upon the results generated by the NLP platform. All collated tweets were anonymised RESULTS We identified and analysed 286,902 tweets posted from UK user accounts from 23 July 2020 to 6 January 2021. The average sentiment score was 50%, suggesting overall neutral sentiment across all tweets over the study period. Major fluctuations in volume and sentiment appeared to coincide with key changes to any local and/or national social-distancing measures. Tweets around mental health were polarising, discussed with both positive and negative sentiment. Key topics of consistent discussion over the study period included the impact of the pandemic on people’s mental health (both positively and negatively), fear and anxiety over lockdowns, and anger and mistrust toward the government. CONCLUSIONS Through the primary use of an AI-based NLP platform, we were able to rapidly mine and analyse emerging health-related insights from UK tweets into how the pandemic may be impacting people’s mental health and well-being. This type of real-time analysed evidence could act as a useful intelligence source that agencies, local leaders, and health care decision makers can potentially draw from, particularly during a health crisis.

Social bots detection in Brazilian presidential elections using natural language processing

2021 ◽  
Author(s):  
Gabriel Estavaringo Ferreira ◽  
Bianca Lima Santos ◽  
Marcelo Torres do Ó ◽  
Rafael Rodrigues Braz ◽  
Luciano Antonio Digiampietri
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Presidential Elections

EXPERIENCE OF DEVELOPED COUNTRIES OF THE WORLD ON REGULATION OF SPORTS AND HEALTH SPHERE AND PROMOTION OF ITS DEVELOPMENT

2021 ◽  
Vol 9 (1) ◽  
pp. 91-100
Author(s):  
Serhii Tsymbaliuk
Keyword(s):  
Comparative Analysis ◽  
Developed Countries ◽  
Scientific Basis ◽  
Organizational Models ◽  
Economic Role ◽  
The World ◽  
New Challenges ◽  
Developed World ◽  
The Impact

The purpose of the article is to study the experience of developed countries in the regulation of sports and health in order to stimulate its development and adaptation to new challenges and threats. In the course of the research the methods of theoretical and comparative analysis were used to reveal the peculiarities of the American and European models of sports and health man-agement; statistical and graphical - to determine the economic role and trends in the sports and health industry in the world, the impact of the pandemic on income from sports. The article develops organizational and economic approaches to intensify the development of sports and recreation. Certain features of organizational models of management, sports legislation, financ-ing, possible tools to stimulate the development of sports and health in the developed world form a scientific basis for substantiating ways to intensify this area.

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