- Abu-Taleb, S. K., and Nilsson, F. Impact of social media on investment decision: A quantitative study which considers information online, online community behaviour, and firm image. Bachelor’s thesis, Umeå University, 2021. S. Özöğür Akyüz et al.
Paper not yet in RePEc: Add citation now
Baresa, S., Bogdan, S., and Ivanovic, Z. Strategy of stock valuation by fundamental analysis. UTMS Journal of Economics 4, 1 (2013), 45–51.
Breaban, A., and Noussair, C. N. Emotional state and market behavior. Review of Finance 22, 1 (2018), 279–309.
- Cakra, Y. E., and Trisedya, B. D. Stock price prediction using linear regression based on sentiment analysis. In 2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) (Depok, Indonesia, 2015), IEEE, pp. 147–154.
Paper not yet in RePEc: Add citation now
- Catelli, R., Fujita, H., De Pietro, G., and Esposito, M. Deceptive reviews and sentiment polarity: Effective link by exploiting BERT. Expert Systems with Applications 209 (2022), 118290.
Paper not yet in RePEc: Add citation now
- Chauhan, P., Sharma, N., and Sikka, G. The emergence of social media data and sentiment analysis in election prediction. Journal of Ambient Intelligence and Humanized Computing 12, 2 (2021), 2601–2627.
Paper not yet in RePEc: Add citation now
Costola, M., Hinz, O., Nofer, M., and Pelizzon, L. Machine learning sentiment analysis, Covid-19 news and stock market reactions. Research in International Business and Finance 64 (2023), 101881.
- Deng, L., and Yu, D. Deep learning: methods and applications. Foundations and Trends in Signal Processing 7, 3–4 (2014), 197–387.
Paper not yet in RePEc: Add citation now
- Dhanasekaren, K., Aluri, S. T., Karthikeyan, N., Baskaran, S. H., and Selvanambi, R. A study on the impact of sentiment analysis on stock market prediction. Recent Advances in Computer Science and Communications 16 (formerly: Recent Patents on Computer Science), 1 (2023), 73–93.
Paper not yet in RePEc: Add citation now
- Ding, X., Zhang, Y., Liu, T., and Duan, J. Using structured events to predict stock price movement: An empirical investigation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2014), pp. 1415–1425.
Paper not yet in RePEc: Add citation now
- Doğan, M., Metin, Ö., Tek, E., Yumuşak, S., and Öztoprak, K. Speculator and influencer evaluation in stock market by using social media. In 2020 IEEE International Conference on Big Data (Big Data) (Atlanta, GA, USA, 2020), IEEE, pp. 4559–4566.
Paper not yet in RePEc: Add citation now
- Fabien, M. (3 November 2019). Natural language processing in French (TAL/NLP) (accessed on 29 November 2019) (in French).
Paper not yet in RePEc: Add citation now
- Ghanem, D., and Rosvall, D. Major world events impact on stock market prices: An event study. Bachelor’s thesis, Department of Business Studies, Uppsalla University, 2014.
Paper not yet in RePEc: Add citation now
- Gilbert, E., and Karahalios, K. Widespread worry and the stock market. In Proceedings of the Fourth International AAAI Conference on web and Social Media, Vol. 4, No. 1 (2010) pp. 58-65.
Paper not yet in RePEc: Add citation now
- Goutte, S., Liu, F., Le, H. V., and von Mettenheim, H.-J. (5 January 2023). ESG investing: A sentiment analysis approach (accessed on 28 December 2023).
Paper not yet in RePEc: Add citation now
- Hasselgren, B., Chrysoulas, C., Pitropakis, N., and Buchanan, W. J. Using social media & sentiment analysis to make investment decisions. Future Internet 15, 1 (2023), 5.
Paper not yet in RePEc: Add citation now
- Hochreiter, S., and Schmidhuber, J. Long short-term memory. Neural computation 9, 8 (1997), 1735–1780.
Paper not yet in RePEc: Add citation now
- Jabeen, A., Afzal, S., Maqsood, M., Mehmood, I., Yasmin, S., Niaz, M. T., and Nam, Y. An LSTM based forecasting for major stock sectors using Covid sentiment. Computers, Materials and Continua 67, 1 (2021), 1191–1206.
Paper not yet in RePEc: Add citation now
- Jena, P. R., and Majhi, R. Are Twitter sentiments during Covid-19 pandemic a critical determinant to predict stock market movements? A machine learning approach. Scientific African 19 (2023), e01480.
Paper not yet in RePEc: Add citation now
- Karlemstrand, R., and Leckström, E. Using Twitter attribute information to predict stock prices, 2021. Working paper version available from arXiv: https://doi.org/10.48550/arXiv.2105.01402.
Paper not yet in RePEc: Add citation now
- Khatri, S. K., and Srivastava, A. Using sentimental analysis in prediction of stock market investment. In 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO) (Noida, India, 2016), IEEE, pp. 566–569.
Paper not yet in RePEc: Add citation now
- Li, J., Bu, H., and Wu, J. Sentiment-aware stock market prediction: A deep learning method. In International Conference on Service Systems and Service Management (Dalian, 2017), IEEE, pp. 1–6.
Paper not yet in RePEc: Add citation now
- Li, X., Xie, H., Chen, L., Wang, J., and Deng, X. News impact on stock price return via sentiment analysis. KnowledgeBased Systems 69 (2014), 14–23.
Paper not yet in RePEc: Add citation now
Liu, H. Leveraging financial news for stock trend prediction with attention-based recurrent neural network, 2018. Working paper version available from arXiv: https://doi.org/10.48550/arXiv.1811.06173.
- Long, W., Song, L., and Tian, Y. A new graphic kernel method of stock price trend prediction based on financial news semantic and structural similarity. Expert Systems with Applications 118 (2019), 411–424.
Paper not yet in RePEc: Add citation now
- Martin, V. Predicting the French stock market using social media analysis. In 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization (Bayonne, France, 2013), IEEE, pp. 3–7.
Paper not yet in RePEc: Add citation now
- Mukherjee, S., Sadhukhan, B., Sarkar, N., Roy, D., and De, S. Stock market prediction using deep learning algorithms. CAAI Transactions on Intelligence Technology 8, 1 (2023), 82–94.
Paper not yet in RePEc: Add citation now
- Nguyen, T. H., Shirai, K., and Velcin, J. Sentiment analysis on social media for stock movement prediction. Expert Systems with Applications 42, 24 (2015), 9603–9611.
Paper not yet in RePEc: Add citation now
- Pathak, A. R., Pandey, M., and Rautaray, S. Topic-level sentiment analysis of social media data using deep learning. Applied Soft Computing 108 (2021), 107440.
Paper not yet in RePEc: Add citation now
- Picasso, A., Merello, S., Ma, Y., Oneto, L., and Cambria, E. Technical analysis and sentiment embeddings for market trend prediction. Expert Systems with Applications 135 (2019), 60–70.
Paper not yet in RePEc: Add citation now
- Porshnev, A., Redkin, I., and Shevchenko, A. Machine learning in prediction of stock market indicators based on historical data and data from Twitter sentiment analysis. In 2013 IEEE 13th International Conference on Data Mining Workshops (Dallas, TX, USA, 2013), IEEE, pp. 440–444. Applications of robust optimization. . . 107
Paper not yet in RePEc: Add citation now
Ragab, M. G., Abdulkadir, S. J., Aziz, N., Al-Tashi, Q., Alyousifi, Y., Alhussian, H., and Alqushaibi, A. A novel one-dimensional CNN with exponential adaptive gradients for air pollution index prediction. Sustainability 12, 23 (2020), 10090.
- Schmitz, H. C., Lutz, B., Wolff, D., and Neumann, D. When machines trade on corporate disclosures: Using text analytics for investment strategies. Decision Support Systems 165 (2023), 113892.
Paper not yet in RePEc: Add citation now
- Shang, L., Xi, H., Hua, J., Tang, H., and Zhou, J. A lexicon enhanced collaborative network for targeted financial sentiment analysis. Information Processing & Management 60, 2 (2023), 103187.
Paper not yet in RePEc: Add citation now
- Shastri, M., Roy, S., and Mittal, M. Stock price prediction using artificial neural model: an application of big data. EAI Endorsed Transactions on Scalable Information Systems 6, 20 (2019), e1.
Paper not yet in RePEc: Add citation now
- Shruthi, J., and Swamy, S. A prior case study of natural language processing on different domain. International Journal of Electrical and Computer Engineering 10, 5 (2020), 4928–4936.
Paper not yet in RePEc: Add citation now
- Singh, T., Bhisikar, S. B., and Kumar, M. Stock market prediction using ensemble learning and sentimental analysis. In Machine Learning, Image Processing, Network Security and Data Sciences: Select Proceedings of 3rd International Conference on MIND 2021 (Singapore, 2023), R. Doriya, B. Soni, A. Shukla and X.-Z. Gao, Eds., vol. 946 of Lecture Notes in Electrical Engineering, Springer, pp. 429–441.
Paper not yet in RePEc: Add citation now
- Turri, A. M., Smith, K. H., and Kemp, E. Developing affective brand commitment through social media. Journal of Electronic Commerce Research 14, 3 (2013), 201–214.
Paper not yet in RePEc: Add citation now
- Vargas, M. R., de Lima, B. S. L. P., and Evsukoff, A. G. Deep learning for stock market prediction from financial news articles. In 2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) ( Annecy, France, 2017), IEEE, pp. 60–65.
Paper not yet in RePEc: Add citation now
- Vu, T. T., Chang, S., Ha, Q. T., and Collier, N. An experiment in integrating sentiment features for tech stock prediction in Twitter. In Proceedings of the Workshop on Information Extraction and Entity Analytics on Social Media Data (Mumbai, India, 2012), The COLING 2012 Organizing Committee, pp. 23–38.
Paper not yet in RePEc: Add citation now
- Wehrmann, J., Becker, W., Cagnini, H. E., and Barros, R. C. A character-based convolutional neural network for language-agnostic Twitter sentiment analysis. In 2017 International Joint Conference on Neural Networks (IJCNN) (Anchorage, AK, USA, 2017), IEEE, pp. 2384–2391.
Paper not yet in RePEc: Add citation now
- Wilson, A. C., Roelofs, R., Stern, M., Srebro, N., and Recht, B. The marginal value of adaptive gradient methods in machine learning. In Advances in Neural Information Processing Systems 30: 31st Annual Conference on Neural Information Processing Systems ( NIPS 2017) (Long Beach, CA, USA, 2017), U. von Luxburg, S. Bengio, R. Fergus, R. Garnett, I. Guyon, H. Wallach and S.V.N. Vishwanathan, Eds., Curran Associates, Inc., pp. 4149–4159.
Paper not yet in RePEc: Add citation now
- Xie, Y., and Jiang, H. Stock market forecasting based on text mining technology: A support vector machine method, 2019. Working paper version available from arXiv: https://doi.org/10.48550/arXiv.1909.12789.
Paper not yet in RePEc: Add citation now
- Xu, F., and Keelj, V. Collective sentiment mining of microblogs in 24-hour stock price movement prediction. In 2014 IEEE 16th Conference on Business Informatics (Geneva, Switzerland, 2014), vol. 2, IEEE, pp. 60–67.
Paper not yet in RePEc: Add citation now
- Yang, X., Loua, M. A., Wu, M., Huang, L., and Gao, Q. Multi-granularity stock prediction with sequential three-way decisions. Information Sciences 621 (2023), 524–544.
Paper not yet in RePEc: Add citation now
- Zhang, X., Qu, S., Huang, J., Fang, B., and Yu, P. Stock market prediction via multi-source multiple instance learning. IEEE Access 6 (2018), 50720–50728.
Paper not yet in RePEc: Add citation now
- Zhao, Y., and Yang, G. Deep learning-based integrated framework for stock price movement prediction. Applied Soft Computing 133 (2023), 109921.
Paper not yet in RePEc: Add citation now