From classification to quantification in tweet sentiment analysis
By Wei Gao, Fabrizio Sebastiani. 2016
71 citations recorded by the source corpus.
Subfields: Artificial Intelligence
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
- Christos Baziotis
- Carlos Castillo
- Fernando Diaz
- Nikos Pelekis
- Christos Doulkeridis
- Emre Kıcıman
- Alexandra Olteanu
- Hamed Zamani
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Risks are also linked to the selection of the objective functions used to express various inference or prediction tasks (Wagstaff, 2012); such as using a wrong objective function that does not match the inference methodology (Gao and Sebastiani, 2016), or one that leads to undesirable behavior durin”
- DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis (2017, methodology): “PCC performed better than CC for Subtask D but far worse than CC for Subtask E.”