Sensing Trending Topics in Twitter
By Luca Maria Aiello, Georgios Petkos, Carlos J. Martín-Dancausa, David P. A. Corney, Symeon Papadopoulos, Ryan Skraba, Ayse Göker, Yiannis Kompatsiaris, Alejandro Jaimes. IEEE transactions on multimedia, 2013
438 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/f82dd04de0f4cbd4ba31f201655a788c6576343f
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
- Eleonora D'Andrea
- Beatrice Lazzerini
- Francesco Marcelloni
- Bart Dhoedt
- Pietro Ducange
- Steven Van Canneyt
- Cedric De Boom
In Information Systems
- Eleonora D'Andrea
- Beatrice Lazzerini
- Francesco Marcelloni
- Bart Dhoedt
- Pietro Ducange
- Steven Van Canneyt
- Cedric De Boom
In Statistical and Nonlinear Physics
Citations in the corpus
- Semantics-driven Event Clustering in Twitter Feeds (2015, methodology): “Alternatively we could represent our tweets using df-idf t vectors, instead of tf-idf vectors, which also consider time aspects of the tweets [1].”
- Real-Time Detection of Traffic From Twitter Stream Analysis (2015, methodology): “The IDF index is a simplified version of the TF-IDF (Term Frequency-IDF) index [38]–[40], where the TF part considers the frequency of a specific stem within each SUM.”