research-article

CrowdPT: Summarizing Crowd Opinions as Professional Analyst

Authors:

Chung-Chi Chen,

Hen-Hsen Huang,

Chia-Wen Tsai,

Hsin-Hsi ChenAuthors Info & Claims

WWW '19: The World Wide Web Conference

Pages 3498 - 3502

https://doi.org/10.1145/3308558.3314122

Published: 13 May 2019 Publication History

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Abstract

This paper demonstrates a novel analytics service, CrowdPT, for capturing the key information, price target (PT), of individual investors on social media. PT, which is mentioned as a conclusion in most of analysts' reports, indicates not only the market sentiment (bullish/bearish) of investors, but also the analysis results. In order to provide the latest opinions of individual investors, we monitor Twitter in real time and update the information in price chart daily. For all component stocks in Dow Jones Industrial Average, textual information from numerous tweets is summarized into a single number, PT, in CrowdPT. Case studies confirm the effectiveness of our analytics service in the financial domain, and show that capturing the PT of individual investors is promising for stock price prediction. The Web API of CrowdPT is also provided for academic purpose.

References

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Chung-Chi Chen, Hen-Hsen Huang, Yow-Ting Shiue, and Hsin-Hsi Chen. 2018. Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting. In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 136-143.

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Cited By

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Chen CHuang HChen HChen CHuang HChen H(2021)FinTech ApplicationsFrom Opinion Mining to Financial Argument Mining10.1007/978-981-16-2881-8_6(73-87)Online publication date: 21-May-2021
https://doi.org/10.1007/978-981-16-2881-8_6
Chen CHuang HTakamura HChen H(2019)Final Report of the NTCIR-14 FinNum Task: Challenges and Current Status of Fine-Grained Numeral Understanding in Financial Social Media DataNII Testbeds and Community for Information Access Research10.1007/978-3-030-36805-0_14(183-192)Online publication date: 28-Nov-2019
https://doi.org/10.1007/978-3-030-36805-0_14

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Published In

WWW '19: The World Wide Web Conference

May 2019

3620 pages

ISBN:9781450366748

DOI:10.1145/3308558

Editors:
Ling Liu
Georgia Tech, USA
,
Ryen White
Microsoft Research, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 13 May 2019

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WWW '19: The Web Conference

May 13 - 17, 2019

CA, San Francisco, USA

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Chen CHuang HChen HChen CHuang HChen H(2021)FinTech ApplicationsFrom Opinion Mining to Financial Argument Mining10.1007/978-981-16-2881-8_6(73-87)Online publication date: 21-May-2021
https://doi.org/10.1007/978-981-16-2881-8_6
Chen CHuang HTakamura HChen H(2019)Final Report of the NTCIR-14 FinNum Task: Challenges and Current Status of Fine-Grained Numeral Understanding in Financial Social Media DataNII Testbeds and Community for Information Access Research10.1007/978-3-030-36805-0_14(183-192)Online publication date: 28-Nov-2019
https://doi.org/10.1007/978-3-030-36805-0_14

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Hedging via Opinion-based Pair Trading Strategy

Analyst Recommendations, Mutual Fund Herding, and Overreaction in Stock Prices

Summarizing User Opinions: A Method for Labeled-data Scarce Product Domains

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Hedging via Opinion-based Pair Trading Strategy

Analyst Recommendations, Mutual Fund Herding, and Overreaction in Stock Prices

Summarizing User Opinions: A Method for Labeled-data Scarce Product Domains

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