TOTEMSS: Topic-based, Temporal Sentiment Summarisation for Twitter
Bo Wang, Maria Liakata, Adam Tsakalidis, Spiros Georgakopoulos Kolaitis, Symeon Papadopoulos, Lazaros Apostolidis, Arkaitz Zubiaga, Rob Procter, Yiannis Kompatsiaris
IJCNLP. 2017.
We present a system for time-sensitive, topic-based summarisation of sentiment around target entities and topics in collections of tweets. We describe the main elements of the system and present two examples of sentiment analysis of topics related to the 2017 UK general election.
@article{wang2017totemss,
title={TOTEMSS: Topic-based, temporal sentiment summarisation for Twitter},
author={Wang, Bo and Liakata, Maria and Tsakalidis, Adam and Georgakopoulos, Agelos and Papadopoulos, Orestis and Apostolidis, Lazaros and Zubiaga, Arkaitz and Procter, Rob and Kompatsiaris, Yiannis},
journal={Proceedings of the IJCNLP 2017},
pages={21--24},
year={2017},
publisher={Association for Computational Linguistics}
}
title={TOTEMSS: Topic-based, temporal sentiment summarisation for Twitter},
author={Wang, Bo and Liakata, Maria and Tsakalidis, Adam and Georgakopoulos, Agelos and Papadopoulos, Orestis and Apostolidis, Lazaros and Zubiaga, Arkaitz and Procter, Rob and Kompatsiaris, Yiannis},
journal={Proceedings of the IJCNLP 2017},
pages={21--24},
year={2017},
publisher={Association for Computational Linguistics}
}