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        <title>Entity Linking within a Social Media Platform: A Case Study on Yelp</title>
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    <abstract>In this paper, we study a new entity linking problem where both the entity mentions and the target entities are within a same social media platform. Compared with traditional entity linking problems that link mentions to a knowledge base, this new problem have less information about the target entities. However, if we can successfully link mentions to entities within a social media platform, we can improve a lot of applications such as comparative study in business intelligence and opinion leader finding. To study this problem, we constructed a dataset called Yelp-EL, where the business mentions in Yelp reviews are linked to their corresponding businesses on the platform. We conducted comprehensive experiments and analysis on this dataset with a learning to rank model that takes different types of features as input, as well as a few state-of-the-art entity linking approaches. Our experimental results show that two types of features that are not available in traditional entity linking: social features and location features, can be very helpful for this task.</abstract>
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%0 Conference Proceedings
%T Entity Linking within a Social Media Platform: A Case Study on Yelp
%A Dai, Hongliang
%A Song, Yangqiu
%A Qiu, Liwei
%A Liu, Rijia
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F dai-etal-2018-entity
%X In this paper, we study a new entity linking problem where both the entity mentions and the target entities are within a same social media platform. Compared with traditional entity linking problems that link mentions to a knowledge base, this new problem have less information about the target entities. However, if we can successfully link mentions to entities within a social media platform, we can improve a lot of applications such as comparative study in business intelligence and opinion leader finding. To study this problem, we constructed a dataset called Yelp-EL, where the business mentions in Yelp reviews are linked to their corresponding businesses on the platform. We conducted comprehensive experiments and analysis on this dataset with a learning to rank model that takes different types of features as input, as well as a few state-of-the-art entity linking approaches. Our experimental results show that two types of features that are not available in traditional entity linking: social features and location features, can be very helpful for this task.
%R 10.18653/v1/D18-1227
%U https://aclanthology.org/D18-1227
%U https://doi.org/10.18653/v1/D18-1227
%P 2023-2032

Markdown (Informal)

[Entity Linking within a Social Media Platform: A Case Study on Yelp](https://aclanthology.org/D18-1227) (Dai et al., EMNLP 2018)

• Entity Linking within a Social Media Platform: A Case Study on Yelp (Dai et al., EMNLP 2018)

ACL

• Hongliang Dai, Yangqiu Song, Liwei Qiu, and Rijia Liu. 2018. Entity Linking within a Social Media Platform: A Case Study on Yelp. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2023–2032, Brussels, Belgium. Association for Computational Linguistics.