I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance
February 05, 2020 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
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Authors
Qi Yang, Aleksandr Farseev, Andrey Filchenkov
arXiv ID
2002.01726
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG,
cs.SI
Citations
7
Venue
AAAI Conference on Artificial Intelligence
Last Checked
4 months ago
Abstract
Nowadays, social networks play a crucial role in human everyday life and no longer purely associated with spare time spending. In fact, instant communication with friends and colleagues has become an essential component of our daily interaction giving a raise of multiple new social network types emergence. By participating in such networks, individuals generate a multitude of data points that describe their activities from different perspectives and, for example, can be further used for applications such as personalized recommendation or user profiling. However, the impact of the different social media networks on machine learning model performance has not been studied comprehensively yet. Particularly, the literature on modeling multi-modal data from multiple social networks is relatively sparse, which had inspired us to take a deeper dive into the topic in this preliminary study. Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks. Our initial experimental results reveal that social network choice impacts the performance and the proper selection of data source is crucial.
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