5:20 PM - 5:40 PM
[1P3-01] Twitter Actuates the Cryptocurrency Market
Keywords:social media, cryptocurrency, social sensor
Social media is not only a sensor but also an actuator. A social sensor can detect various social phenomena or trends by using the data obtained from social media. Though the information from social sensors has vastly enhanced our potential to observe and predict real-world phenomena, the causality from the social media itself to the real world has not been studied to date. Meanwhile, recent trends in SNS-driven consumer behavior, such as taking beautiful photos for Instagram, so-called "Instagenic," have further highlighted the importance of studying the causality from social media to the real world.
This paper demonstrates a new concept of social actuator. We introduce internal states, which represent the states of the social media users influenced by others, and show how to address the confounding structure in the inference of causality from social media to the real world. Using the results of our experiments on Twitter data and cryptocurrency-market data, we show that our proposed method can detect the influences between the users on social media, and describe the causation from Twitter to the cryptocurrency market. Finally, we discuss the effectiveness of the proposed method for different datasets and suggest that we all have the potential to impact the real world through social media either intentionally or unintentionally.
This paper demonstrates a new concept of social actuator. We introduce internal states, which represent the states of the social media users influenced by others, and show how to address the confounding structure in the inference of causality from social media to the real world. Using the results of our experiments on Twitter data and cryptocurrency-market data, we show that our proposed method can detect the influences between the users on social media, and describe the causation from Twitter to the cryptocurrency market. Finally, we discuss the effectiveness of the proposed method for different datasets and suggest that we all have the potential to impact the real world through social media either intentionally or unintentionally.