Deep Twitter diving: exploring topical groups in microblogs at scale
By Parantapa Bhattacharya, Saptarshi Ghosh, J. Kulshrestha, Mainack Mondal, Muhammad Bilal Zafar, Niloy Ganguly, Krishna P. Gummadi. 2014
42 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Mark Crovella
- Alan Mislove
- Krishna P. Gummadi
- Carlos Castillo
- Fernando Diaz
- Balachander Krishnamurthy
- Muhammad Ahmad Bashir
- Bimal Viswanath
In Statistical and Nonlinear Physics
- Alexandra Olteanu
- Carlos Castillo
- Fernando Diaz
- Emre Kıcıman
- Alan Mislove
- Balachander Krishnamurthy
- Krishna P. Gummadi
- Mark Crovella
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “For instance, Bhattacharya et al. (2014) found that on Twitter “expert” users tend to create content mainly on their topic of expertise, while Zafar et al. (2015) show how focusing the sampling of content on “expert” users biases the resulting sample toward more trustworthy and high-quality content.”
- Towards Detecting Anomalous User Behavior in Online Social Networks (2014, methodology): “We find low-effective dimension in each dataset as discussed below.”