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  pages={806--841},
  year={2023},
  publisher={Wiley Online Library}
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@article{fatouros2023transforming,
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  year={2023},
  publisher={Elsevier}
}

@inproceedings{sousa2019bert,
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  pages={1597--1601},
  year={2019},
  organization={IEEE}
}
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  organization={PMLR}
}
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}
@article{kabir2025lstm,
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@article{sohangir2018big,
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@article{dettmers2022gpt3,
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@article{morris2020textattack,
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@article{naresh2021efficient,
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  pages={725--731},
  year={2021},
  publisher={Springer}
}

@article{lutz2018sentence,
  title={Sentence-level sentiment analysis of financial news using distributed text representations and multi-instance learning},
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  year={2018}
}

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  title={Comparative analysis using machine learning techniques for fine grain sentiments},
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  journal={Journal on Artificial Intelligence},
  volume={4},
  number={1},
  pages={49--60},
  year={2022}
}

@article{baby2021leukocyte,
  title={Leukocyte classification based on feature selection using extra trees classifier: Atransfer learning approach},
  author={Baby, Diana and Devaraj, Sujitha Juliet and Hemanth, Jude and others},
  journal={Turkish Journal of Electrical Engineering and Computer Sciences},
  volume={29},
  number={8},
  pages={2742--2757},
  year={2021}
}

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@article{bose2015generalized,
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  journal={Pattern Recognition},
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@article{malo2014good,
  title={Good debt or bad debt: Detecting semantic orientations in economic texts},
  author={Malo, Pekka and Sinha, Ankur and Korhonen, Pekka and Wallenius, Jyrki and Takala, Pyry},
  journal={Journal of the Association for Information Science and Technology},
  volume={65},
  number={4},
  pages={782--796},
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@article{mishev2020evaluation,
  title={Evaluation of sentiment analysis in finance: from lexicons to transformers},
  author={Mishev, Kostadin and Gjorgjevikj, Ana and Vodenska, Irena and Chitkushev, Lubomir T and Trajanov, Dimitar},
  journal={IEEE access},
  volume={8},
  pages={131662--131682},
  year={2020},
  publisher={IEEE}
}


@article{aslam2022sentiment,
  title={Sentiment analysis and emotion detection on cryptocurrency related tweets using ensemble LSTM-GRU model},
  author={Aslam, Naila and Rustam, Furqan and Lee, Ernesto and Washington, Patrick Bernard and Ashraf, Imran},
  journal={Ieee Access},
  volume={10},
  pages={39313--39324},
  year={2022},
  publisher={IEEE}
}

@article{ahmad2023sentiment,
  title={Sentiment analysis of financial textual data using machine learning and deep learning models},
  author={Ahmad, Hero O and Umar, Shahla U},
  journal={Informatica},
  volume={47},
  number={5},
  year={2023}
}


@article{leippold2023sentiment,
  title={Sentiment spin: Attacking financial sentiment with GPT-3},
  author={Leippold, Markus},
  journal={Finance Research Letters},
  volume={55},
  pages={103957},
  year={2023},
  publisher={Elsevier}
}

@article{daudert2021exploiting,
  title={Exploiting textual and relationship information for fine-grained financial sentiment analysis},
  author={Daudert, Tobias},
  journal={Knowledge-Based Systems},
  volume={230},
  pages={107389},
  year={2021},
  publisher={Elsevier}
}

@article{consoli2022fine,
  title={Fine-grained, aspect-based sentiment analysis on economic and financial lexicon},
  author={Consoli, Sergio and Barbaglia, Luca and Manzan, Sebastiano},
  journal={Knowledge-Based Systems},
  volume={247},
  pages={108781},
  year={2022},
  publisher={Elsevier}
}

@article{yadav2020sentiment,
  title={Sentiment analysis of financial news using unsupervised approach},
  author={Yadav, Anita and Jha, CK and Sharan, Aditi and Vaish, Vikrant},
  journal={Procedia Computer Science},
  volume={167},
  pages={589--598},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{xing2020financial,
  title={Financial sentiment analysis: an investigation into common mistakes and silver bullets},
  author={Xing, Frank and Malandri, Lorenzo and Zhang, Yue and Cambria, Erik},
  booktitle={Proceedings of the 28th international conference on computational linguistics},
  pages={978--987},
  year={2020}
}

@article{du2023incorporating,
  title={Incorporating multiple knowledge sources for targeted aspect-based financial sentiment analysis},
  author={Du, Kelvin and Xing, Frank and Cambria, Erik},
  journal={ACM Transactions on Management Information Systems},
  volume={14},
  number={3},
  pages={1--24},
  year={2023},
  publisher={ACM New York, NY}
}

@inproceedings{zhang2023enhancing,
  title={Enhancing financial sentiment analysis via retrieval augmented large language models},
  author={Zhang, Boyu and Yang, Hongyang and Zhou, Tianyu and Ali Babar, Muhammad and Liu, Xiao-Yang},
  booktitle={Proceedings of the fourth ACM international conference on AI in finance},
  pages={349--356},
  year={2023}
}

@article{vstrimaitis2021financial,
  title={Financial context news sentiment analysis for the Lithuanian language},
  author={{\v{S}}trimaitis, Rokas and Stefanovi{\v{c}}, Pavel and Ramanauskait{\.e}, Simona and Slotkien{\.e}, Asta},
  journal={Applied Sciences},
  volume={11},
  number={10},
  pages={4443},
  year={2021},
  publisher={MDPI}
}

@article{liapis2021multi,
  title={A multi-method survey on the use of sentiment analysis in multivariate financial time series forecasting},
  author={Liapis, Charalampos M and Karanikola, Aikaterini and Kotsiantis, Sotiris},
  journal={Entropy},
  volume={23},
  number={12},
  pages={1603},
  year={2021},
  publisher={MDPI}
}


@article{hansen2022alternative,
  title={Alternative data and sentiment analysis: Prospecting non-standard data in machine learning-driven finance},
  author={Hansen, Kristian Bondo and Borch, Christian},
  journal={Big Data \& Society},
  volume={9},
  number={1},
  pages={20539517211070701},
  year={2022},
  publisher={Sage Publications Sage UK: London, England}
}

@article{passalis2022multisource,
  title={Multisource financial sentiment analysis for detecting Bitcoin price change indications using deep learning},
  author={Passalis, Nikolaos and Avramelou, Loukia and Seficha, Solon and Tsantekidis, Avraam and Doropoulos, Stavros and Makris, Giorgos and Tefas, Anastasios},
  journal={Neural Computing and Applications},
  volume={34},
  number={22},
  pages={19441--19452},
  year={2022},
  publisher={Springer}
}

@article{valle2022does,
  title={Does twitter affect stock market decisions? financial sentiment analysis during pandemics: A comparative study of the h1n1 and the covid-19 periods},
  author={Valle-Cruz, David and Fernandez-Cortez, Vanessa and L{\'o}pez-Chau, Asdr{\'u}bal and Sandoval-Almaz{\'a}n, Rodrigo},
  journal={Cognitive computation},
  volume={14},
  number={1},
  pages={372--387},
  year={2022},
  publisher={Springer}
}

@article{hartmann2023more,
  title={More than a feeling: Accuracy and application of sentiment analysis},
  author={Hartmann, Jochen and Heitmann, Mark and Siebert, Christian and Schamp, Christina},
  journal={International Journal of Research in Marketing},
  volume={40},
  number={1},
  pages={75--87},
  year={2023},
  publisher={Elsevier}
}


@article{zhang2023emotion,
  title={Emotion fusion for mental illness detection from social media: A survey},
  author={Zhang, Tianlin and Yang, Kailai and Ji, Shaoxiong and Ananiadou, Sophia},
  journal={Information Fusion},
  volume={92},
  pages={231--246},
  year={2023},
  publisher={Elsevier}
}

@article{singh2022reinforcement,
  title={How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries--A review and research agenda},
  author={Singh, Vinay and Chen, Shiuann-Shuoh and Singhania, Minal and Nanavati, Brijesh and Gupta, Agam and others},
  journal={International Journal of Information Management Data Insights},
  volume={2},
  number={2},
  pages={100094},
  year={2022},
  publisher={Elsevier}
}

@article{leelawat2022twitter,
  title={Twitter data sentiment analysis of tourism in Thailand during the COVID-19 pandemic using machine learning},
  author={Leelawat, Natt and Jariyapongpaiboon, Sirawit and Promjun, Arnon and Boonyarak, Samit and Saengtabtim, Kumpol and Laosunthara, Ampan and Yudha, Alfan Kurnia and Tang, Jing},
  journal={Heliyon},
  volume={8},
  number={10},
  year={2022},
  publisher={Elsevier}
}

@article{kumar2022past,
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  journal={Annals of Operations Research},
  pages={1--44},
  year={2022},
  publisher={Springer}
}

@article{alsayat2022improving,
  title={Improving sentiment analysis for social media applications using an ensemble deep learning language model},
  author={Alsayat, Ahmed},
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  volume={47},
  number={2},
  pages={2499--2511},
  year={2022},
  publisher={Springer}
}

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@article{chang2022melanoma,
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  year={2019}
}
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  title={Visbert: Hidden-state visualizations for transformers},
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  year={2019}
}

@article{arrieta2020explainable,
  title={Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI},
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  publisher={Elsevier}
}
@article{shao2024linearizing,
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  year={2024}
}
@inproceedings{ribeiro2018anchors,
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  year={2018}
}

@article{lundberg2017unified,
  title={A unified approach to interpreting model predictions},
  author={Lundberg, Scott M and Lee, Su-In},
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  volume={30},
  year={2017}
}

@article{sinha2022sentfin,
  title={SEntFiN 1.0: Entity-aware sentiment analysis for financial news},
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  volume={73},
  number={9},
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}

@article{Malo2014GoodDO,
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@inproceedings{ribeiro2016should,
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  pages={4773--4781},
  year={2022},
  publisher={Elsevier}
}



// Abir

@article{adhikari2023explainable,
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  journal={Neural Networks},
  volume={164},
  pages={115--123},
  year={2023},
  publisher={Elsevier}
}

@article{rizinski2024sentiment,
  title={Sentiment Analysis in Finance: From Transformers Back to eXplainable Lexicons (XLex)},
  author={Rizinski, Maryan and Peshov, Hristijan and Mishev, Kostadin and Jovanovik, Milos and Trajanov, Dimitar},
  journal={IEEE Access},
  year={2024},
  publisher={IEEE}
}

@inproceedings{makridis2023xai,
  title={XAI for time-series classification leveraging image highlight methods},
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  year={2023},
  organization={Springer}
}

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@inproceedings{du2023finsenticnet,
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  booktitle={2023 IEEE Symposium Series on Computational Intelligence (SSCI)},
  pages={109--114},
  year={2023},
  organization={IEEE}
}

@article{chang2022predicting,
  title={Predicting aspect-based sentiment using deep learning and information visualization: The impact of COVID-19 on the airline industry},
  author={Chang, Yung-Chun and Ku, Chih-Hao and Le Nguyen, Duy-Duc},
  journal={Information \& Management},
  volume={59},
  number={2},
  pages={103587},
  year={2022},
  publisher={Elsevier}
}



@article{thompson2020computational,
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@article{jordan2015machine,
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@inproceedings{xu2024ai,
  title={AI-BASED RISK PREDICTION AND MONITORING IN FINANCIAL FUTURES AND SECURITIES MARKETS},
  author={Xu, Jiahao and Zhu, Baixin and Jiang, Wei and Cheng, Qishuo and Zheng, Haotian},
  booktitle={The 13th International scientific and practical conference “Information and innovative technologies in the development of society”(April 02--05, 2024) Athens, Greece. International Science Group. 2024. 321 p.},
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  year={2024}
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@article{go2020analysis,
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  author={Go, Eun Jung and Moon, Junhwan and Kim, Jinhwa},
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  volume={25},
  number={1},
  pages={102--117},
  year={2020},
  publisher={Seoul: People \& Global Business Association (P\&GBA)}
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@inproceedings{ying2019overview,
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}