Social data: Biases, methodological pitfalls, and ethical boundaries
Social data in digital form—including user-generated content, expressed or implicit relations
between people, and behavioral traces—are at the core of popular applications and …
between people, and behavioral traces—are at the core of popular applications and …
A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks
Twitter is the third most popular worldwide Online Social Network (OSN) after Facebook and
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …
[图书][B] Multimodality: Foundations, research and analysis–A problem-oriented introduction
This textbook provides the first foundational introduction to the practice of analysing
multimodality, covering the full breadth of media and situations in which multimodality needs …
multimodality, covering the full breadth of media and situations in which multimodality needs …
Searching for superspreaders of information in real-world social media
A number of predictors have been suggested to detect the most influential spreaders of
information in online social media across various domains such as Twitter or Facebook. In …
information in online social media across various domains such as Twitter or Facebook. In …
Building a large-scale corpus for evaluating event detection on twitter
Despite the popularity of Twitter for research, there are very few publicly available corpora,
and those which are available are either too small or unsuitable for tasks such as event …
and those which are available are either too small or unsuitable for tasks such as event …
Probabilistic graphical models in modern social network analysis
The advent and availability of technology has brought us closer than ever through social
networks. Consequently, there is a growing emphasis on mining social networks to extract …
networks. Consequently, there is a growing emphasis on mining social networks to extract …
Recurrent neural network (RNN) to analyse mental behaviour in social media
HA Bouarara - International Journal of Software Science and …, 2021 - igi-global.com
A recent British study of people between the ages of 14 and 35 has shown that social media
has a negative impact on mental health. The purpose of the paper is to detect people with …
has a negative impact on mental health. The purpose of the paper is to detect people with …
A longitudinal assessment of the persistence of twitter datasets
A Zubiaga - Journal of the Association for Information Science …, 2018 - Wiley Online Library
Social media datasets are not always completely replicable. Having to adhere to
requirements of platforms such as Twitter, researchers can only release a list of unique …
requirements of platforms such as Twitter, researchers can only release a list of unique …
[PDF][PDF] Real-time detection, tracking, and monitoring of automatically discovered events in social media
We introduce ReDites, a system for realtime event detection, tracking, monitoring and
visualisation. It is designed to assist Information Analysts in understanding and exploring …
visualisation. It is designed to assist Information Analysts in understanding and exploring …
[PDF][PDF] The million musical tweets dataset: What can we learn from microblogs
ABSTRACT Microblogs and Social Media applications are continuously growing in spread
and importance. Users of Twitter, the currently most popular platform for microblogging …
and importance. Users of Twitter, the currently most popular platform for microblogging …