Social Media Mining: An Introduction
By Reza Zafarani, Mohammad Ali Abbasi, Huan Liu. 2014
632 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/7a6b0e84893186577f3602691708d77fdb6048f9
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
- Jiliang Tang
- Charu C. Aggarwal
- Huan Liu
- Yi Chang
- Xinyi Zhou
- Hossein Hassani
- Maedeh Taj Mazinani
- Stephane Unger
In Information Systems
- Xinyi Zhou
- Charu C. Aggarwal
- Jiliang Tang
- Huan Liu
- Yi Chang
- Hossein Hassani
- Maedeh Taj Mazinani
- Stephane Unger
In Statistical and Nonlinear Physics
Citations in the corpus
- Text Mining in Big Data Analytics (2020, background): “Blog mining, furthermore, overlaps with features of social media mining [79,80].”
- A Survey of Signed Network Mining in Social Media (2015, methodology): “d Networks in Social Media The problem of mining unsigned networks in social media (or networks with only positive links) has been extensively studied for decades [Knoke and Yang 2008; Aggarwal 2011; Zafarani et al. 2014]. However, mining signed networks requires dedicated methods because it cannot ”
- A Survey of Fake News (2020, background): “The rise of social media and its popularity also plays an essential role in this surge of interest [Olteanu et al. 2019; Zafarani et al. 2014].”
- Recommender Systems (2016, neutral): “Each of the traditional problems of ranking, node classification, and link prediction [22, 656] can be viewed as a structural recommendation problem in social networks.”