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The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach

https://doi.org/10.1007/978-3-030-79474-3_1
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18/18 checkable references clean · checked 2026-08-09

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

9 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 18 checked references that resolve
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Analyzing stock market trends using social media user moods and social influence
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Efficient Market Hypothesis And Stock Market Anomalies: Empirical Evidence In Four European Countries
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Random Walk in Emerging Asian Stock Markets
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A Survey of Opinion Mining and Sentiment Analysis
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A quantitative stock prediction system based on financial news
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Textual analysis of stock market prediction using breaking financial news
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Twitter mood predicts the stock market
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Sentiment Analysis on News Articles for Stocks
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Stock price prediction using linear regression based on sentiment analysis
resolves10.1109/ACCESS.2019.2946594
Target-Dependent Sentiment Classification With BERT
resolves10.1109/SCOPES.2016.7955659
Sentiment analysis of Twitter data for predicting stock market movements
resolves10.18653/v1/P18-1183
Stock Movement Prediction from Tweets and Historical Prices
resolves10.1371/journal.pone.0230442
Question classification based on Bloom’s taxonomy cognitive domain using modified TF-IDF and word2vec
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Biased TextRank: Unsupervised Graph-Based Content Extraction
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Examining the evolution of the Twitter elite network
The 9 references without a DOI — listed, not checked
no DOI — not checkedAggarwal, U., Saxena, A., Herald, S.: Artificial intelligence review in stock markets. Int. J. Res. Eng. Sci. Manag. 2(11), 92–95 (2019)
no DOI — not checkedKumar, H., Jawa, R.: Efficient market hypothesis and calendar effects: empirical evidences from the Indian stock markets. Bus. Analyst 37(2), 145–160 (2017)
no DOI — not checkedDash, M.: Testing the random walk hypothesis in the Indian stock market using ARIMA modelling. J. Appl. Manag. Investments 8(2), 71–77 (2019)
no DOI — not checkedNasr, N., Farhadi Sartangi, M., Madahi, Z.: A fuzzy random walk technique to forecasting volatility of Iran stock exchange index. Adv. Math. Finan. Appl. 4(1), 15–30 (2019)
no DOI — not checkedMittal, A., Goel, A.: Stock Prediction Using Twitter Sentiment Analysis. Standford University, CS229 (2012). Available online. http://cs229.stanford.edu/proj2011/GoelMittalStockMarketPredictionUsingTwitterSentimentAnalysis.pdf. Cited 23 June 2021
no DOI — not checkedLee, H., Surdeanu, M., MacCartney, B., Jurafsky, D.: On the importance of text analysis for stock price prediction. In: The 9th International Conference on Language Resources and Evaluation. LREC 2014, pp. 26–31. Reykjavik, Iceland (2014)
no DOI — not checkedBeckman, M.D., Çetinkaya-Rundel, M., Horton, N.J., Rundel, C.W., Sullivan, A.J., Tackett, M.: Implementing version control with Git and GitHub as a learning objective in statistics and data science courses. J. Stat. Educ. 29(Sup 1), 1–35 (2020)
no DOI — not checkedBo, Y., Liu, Y., Li, H.: Sentiment classification in Chinese microblogs: lexicon-based and learning-based approaches. Int. Proc. Econ. Dev. Res. 68(1), 1–5 (2013)
no DOI — not checkedFulian, Y., Wang, Y., Liu, J., Lin, L.: The construction of sentiment lexicon based on context-dependent part-of-speech chunks for semantic disambiguation. IEEE Access 8(1), 63359–63367 (2020)
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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