What is Twitter
By Rizal Setya Perdana. 2013
1,528 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/130b32280d64422971c9bf9866b047dc824e2047
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Jure Leskovec
- Charu C. Aggarwal
- Emilio Ferrara
- Philip S. Yu
- Kristina Lerman
- Bernhard Schölkopf
- Manuel Gomez-Rodriguez
- Jie Tang
Citations in the corpus
- Streaming graph partitioning for large distributed graphs (2012, methodology): “We used two large social networks (LiveJournal [26] and Twitter [21]) to evaluate our heuristics in a real system in Section 6.”
- FRAUDAR: Bounding Graph Fraud in the Face of Camouflage (2016, background): “47 billion follows; it was extracted in July 2009 and first used in [16].”
- Controlling edge dynamics in complex networks (2011, background): “47× 10(9) [27] A is followed by B communication 32.”
- Everyone's an influencer: quantifying influence on twitter (2011, background): “page rank) or the number of direct, explicit retweets, we measure influence in terms of the size of the entire diffusion tree associated with each event (Kwak et al [18] also compute what they call “retweet trees” but they do not use them as a measure of influence).”
- Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads (2015, background): “This broadens the scope and diversity of information that one can get from social media and sometimes may even lead to stories breaking before they appear in mainstream media outlets [Kwak et al., 2010].”
- Hip and trendy: Characterizing emerging trends on Twitter (2011, methodology): “This source of trend data is commonly used in research efforts related to trends onTwitter (e.g., Kwak et al., 2010; Cheong & Lee, 2009).”
- Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll (2015, background): “The majority of the topics trending on Twitter are headlines or persistent news [23], making Twitter a valuable source for studying climate change opinions.”
- GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media (2020, background): “However, most users on social media tend to simply reshare the source story without leaving any comments (Kwak et al., 2010).”