An Approach to Enhance Business Intelligence and Operations by Sentimental Analysis

Srinivasan, Satish; Shah, Pooja; Sedhai, Surendra

doi:10.33168/jsms.2021.0302

Cited by 5 publications

(6 citation statements)

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“…Text mining is mainly used for research on company performance disclosure, audit reports, and listed company conference calls. Predictions based on text mining are just emerging to be investigated rigorously in the recent years [21][22]. Antonina [23] used language analysis methods to study the information, style, language and readability of financial reports of leading companies in the telecommunications industry.…”

Section: Methods Based On Financial Textsmentioning

confidence: 99%

A Hybrid CNN and LSTM based Model for Financial Crisis Prediction

2024

Teh. vjesn.

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The detection and prediction of financial crises in listed companies are crucial for investors to mitigate potential losses. Traditional prediction methods primarily rely on financial indicators, yet they often overlook valuable insights hidden in financial text. To address this limitation, our study explores the integration of financial indicators and financial text from annual reports to enhance financial crisis prediction. We propose a two-step approach, leveraging a Convolutional Neural Network (CNN) model to extract features from financial indicators and utilizing a Long Short-Term Memory (LSTM) network with attention mechanism to capture the underlying semantics in financial text. Subsequently, we combine the extracted features from both sources for effective classification. Through extensive experiments with various models, we demonstrate the efficacy of our combined approach in achieving optimal prediction results. Our findings highlight the importance of considering financial text alongside traditional financial indicators for enhanced financial crisis detection and prediction. The proposed methodology contributes to the existing literature and offers valuable insights for investors and financial analysts seeking more accurate and comprehensive risk assessment tools.

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Section: Methods Based On Financial Textsmentioning

confidence: 99%

A Hybrid CNN and LSTM based Model for Financial Crisis Prediction

2024

Teh. vjesn.

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“…The development of information technology, primarily the phenomenon of using social media in recent years, has been overgrown (Srinivasan et al, 2021). The ease of accessing all forms of information is now shifting people's habits of using social media (Prasetyo & Purnamasari, 2021).…”

Section: Social Media For Companiesmentioning

confidence: 99%

Regional Bank customer relationship management model through Public Relations functions

Sri Wahyuningsih,

Rochayanti,

Lestari

2024

J. Commun.

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The banking industry, in practice, was established as the community's economic foundation that provides financial services expected to restore and enhance national and regional economic growth. Bank BPD DIY has a strategic role as a government partner and a motor accelerator of regional development in the Special Region of Yogyakarta. State civil apparatus (ASN) DIY is required to use Bank BPD DIY; it is necessary for customer relationship management (customer). This study aimed to find a model of customer relationship management of regional banks through public relations functions. This research uses a descriptive qualitative approach with a case study method. The results of this study indicate that the customer relationship management model at Bank BPD DIY is carried out through three aspects. The first is to provide excellent service (excellent service), which is implemented by implementing the main values of Bank BPD DIY, namely respect, accuracy, modernity, trust, and reliability (friendly), providing funds and credit services, mobile banking, and customer service, and call center. Second, build customer satisfaction and loyalty through programs that provide promos, giveaways, sweepstakes, birthday greetings, and Corporate Social Responsibility. Third, develop good relationships with consumers through the use of social media such as Facebook, Instagram, Twitter, and WhatsApp broadcasts, organizing events, as well as providing sponsorship assistance in the form of products and cash.

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“…Furthermore, machine learning began to be massively used in several cases. Machine learning's primary function in developing and automating text analytics is to advance and construct such parts of speech as named entity recognition (NER) and sentiment analysis (Srinivasan et al ., 2021). They used commonly used machine learning tools, such as Support Vector Machine (SVM), Random Forest classifier, extreme gradient boosting (XGBoost), logistic regression, Word2Vec, Gensim, etc.…”

Section: Introductionmentioning

confidence: 99%

Automatic essay scoring for discussion forum in online learning based on semantic and keyword similarities

Dhini,

Girsang,

Sufandi

et al. 2023

AAOUJ

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PurposeThe authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.Design/methodology/approachThe development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.FindingsThe multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.Originality/valueThis study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

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An Approach to Enhance Business Intelligence and Operations by Sentimental Analysis

Cited by 5 publications

References 0 publications

A Hybrid CNN and LSTM based Model for Financial Crisis Prediction

A Hybrid CNN and LSTM based Model for Financial Crisis Prediction

Regional Bank customer relationship management model through Public Relations functions

Automatic essay scoring for discussion forum in online learning based on semantic and keyword similarities

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