A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks

D Antonakaki, P Fragopoulou, S Ioannidis - Expert systems with …, 2021 - Elsevier
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 …

Influence maximization in unknown social networks: Learning policies for effective graph sampling

H Kamarthi, P Vijayan, B Wilder, B Ravindran… - arXiv preprint arXiv …, 2019 - arxiv.org
A serious challenge when finding influential actors in real-world social networks is the lack
of knowledge about the structure of the underlying network. Current state-of-the-art methods …

Characterizing speed and scale of cryptocurrency discussion spread on reddit

M Glenski, E Saldanha, S Volkova - The World Wide Web Conference, 2019 - dl.acm.org
Cryptocurrencies are a novel and disruptive technology that has prompted a new approach
to how currencies work in the modern economy. As such, online discussions related to …

Fake news detection on twitter using propagation structures

M Meyers, G Weiss, G Spanakis - … , The Netherlands, October 26–27, 2020 …, 2020 - Springer
The growth of social media has revolutionized the way people access information. Although
platforms like Facebook and Twitter allow for a quicker, wider and less restricted access to …

Modelling of trends in twitter using retweet graph dynamics

M Ten Thij, T Ouboter, D Worm, N Litvak… - Algorithms and Models …, 2014 - Springer
In this paper we model user behaviour in Twitter to capture the emergence of trending
topics. For this purpose, we first extensively analyse tweet datasets of several different …

Multi-perspective User2Vec: Exploiting re-pin activity for user representation learning in content curation social network

H Liu, L Wu, D Zhang, M Jian, X Zhang - signal Processing, 2018 - Elsevier
Content curation social networks (CCSN) develop rapidly. Pinterest and Huaban are two
typical CCSNs. Recently, there is active research on CCSNs. As a kind of content based …

Utilizing the average node degree to assess the temporal growth rate of Twitter

D Antonakaki, S Ioannidis, P Fragopoulou - Social Network Analysis and …, 2018 - Springer
Several models have been proposed that describe the evolution of the graph properties of
many online social networks (OSNs) and explain the behavior of their users. These models …

Towards feature selection for cascade growth prediction on twitter

S Elsharkawy, G Hassan, T Nabhan… - Proceedings of the 10th …, 2016 - dl.acm.org
On online social networks such as Twitter, retweeting allows users to share a variety of
content to their own followers. As tweets are retweeted from user to user, large cascades of …

Twitter response to Munich July 2016 attack: Network analysis of influence

I Bermudez, D Cleven, R Gera, ET Kiser… - Frontiers in big …, 2019 - frontiersin.org
Social Media platforms in Cyberspace provide communication channels for individuals,
businesses, as well as state and non-state actors (ie, individuals and groups) to conduct …

DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies

PW Chan - arXiv preprint arXiv:2203.08144, 2022 - arxiv.org
Extreme pricing anomalies may occur unexpectedly without a trivial cause, and equity
traders typically experience a meticulous process to source disparate information and …