Skip to main content
SpringerLink
Log in

Business boosting through sentiment analysis using Artificial Intelligence approach

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

In the recent years, Artificial Intelligence has conquered every field whether it is health sector, financial sector, satellite system, farming sector and many more. Artificial Intelligence has enhanced the performance of all these sectors. In this paper, the focus will be on business performance and the AI methods will be applied in the form of machine learning and deep learning. This paper will present how Artificial Intelligence has enhance the business through the sentiment analysis. The work has also discussed the sentiment analysis approach for the business applications. The paper has covered all the aspects with respect to artificial intelligence in the business domain with its advantages for enhancing the performance of the business. The work has also described the natural language processing for performing the sentiment analysis through which business performance can be boosted.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Abdul RJ, Chinmay C, Celestine W (2021) Exploratory data analysis, classification, comparative analysis, case severity detection, and Internet of Things in COVID-19 telemonitoring for smart hospitals. J Exp Theor Artif Intell 1–24. https://doi.org/10.1080/0952813X.2021.1960634

  • Alita D, Priyanta S, Rokhman N (2019) Analysis of emoticon and sarcasm effect on sentiment analysis of Indonesian language on twitter. J Inf Syst Eng Bus Intell 5(2). https://doi.org/10.20473/jisebi.5.2.100-109

  • Arya P, Bhagat A, Nair R (2019) Improved performance of machine learning algorithms via ensemble learning methods of sentiment analysis. Int J Emerg Technol

  • Borges AFS, Laurindo FJB, Spínola MM, Gonçalves RF, Mattos CA (2021) The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. Int J Inf Manage 57. https://doi.org/10.1016/j.ijinfomgt.2020.102225

  • Caner S, Bhatti F (2020) A conceptual framework on defining businesses strategy for artificial intelligence. Contemp Manag Res 16(3). https://doi.org/10.7903/CMR.19970

  • Cioffi R, Travaglioni M, Piscitelli G, Petrillo A, de Felice F (2020) Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability (Switzerland) 12(2). https://doi.org/10.3390/su12020492

  • Gambín J (2014) Evolution of cloud-based translation memory. MultiLingual, no. April/May

  • Gantz JF, Murray G, Vesset D, Schubmehl D, Wardley M (2017) A trillion-dollar boost: the economic impact of AI on customer relationship management. Sales Force Publication, vol 12, no June 2017

  • Jorge-Martinez D, Butt SA, Onyema EM, Chakraborty C, Shaheen Q, De-La-Hoz-Franco E, Ariza-Colpas P (2021) Artificial intelligence-based Kubernetes container for scheduling nodes of energy composition. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-021-01195-8

    Article  Google Scholar 

  • Kumar A, Abhishek K, Chakraborty C, Kryvinska N (2021) Deep learning and Internet of Things based lung ailment recognition through coughing spectrograms. IEEE Access 9. https://doi.org/10.1109/ACCESS.2021.3094132

  • Kumar A, Dabas V, Hooda P (2018) Text classification algorithms for mining unstructured data: a SWOT analysis. Int J Inf Technol. https://doi.org/10.1007/s41870-017-0072-1

    Article  Google Scholar 

  • Kumar J, Konar R, Balasubramanian K (2020) The impact of social media on consumers’ purchasing behavior in Malaysian restaurants. J Spatial Organ Dyn VIII(3):197-216

    Google Scholar 

  • Liu L, Dzyabura D, Mizik N (2020) Visual listening in: extracting brand image portrayed on social media. Market Sci 39(4). https://doi.org/10.1287/mksc.2020.1226

  • Marr B, Ward M (2019) Artificial intelligence in practice: how 50 successful companies used artificial intelligence to solve problems. Wley

  • Monaghan P, Mattock K, Davies RAI, Smith AC (2015) Gavagai is as Gavagai does: learning nouns and verbs from cross-situational statistics. Cognit Sci 39(5). https://doi.org/10.1111/cogs.12186

  • Montes JM, Larios VM, Avalos M, Ramírez CE (2018) Applying blockchain to supply chain operations at IBM implementing agile practices in a smart city environment. Res Comput Sci 147(2). https://doi.org/10.13053/rcs-147-2-5

  • Moraru A, Ursachi C, Helerea E (2020) A new washable UHF RFID tag: design, fabrication and assessment. Sensors (Switzerland) 20(12). https://doi.org/10.3390/s20123451

  • Morozov V, Mezentseva O, Kolomiiets A, Proskurin M (2022) Predicting customer churn using machine learning in IT startups. in Lecture Notes on Data Engineering and Communications Technologies, vol 77. https://doi.org/10.1007/978-3-030-82014-5_45

  • Nair R, Bhagat A (2018) An application of big data analytics in road transportation. https://doi.org/10.4018/978-1-5225-3870-7.ch003

  • Nair R, Bhagat A (2018) A life cycle on processing large dataset—LCPL Rajit Nair 179(53):27–34

  • Nair R, Bhagat A (2019) An application of blockchain in stock market. https://doi.org/10.4018/978-1-7998-0186-3.ch006

  • Newswire PR (2016) Intelligent Virtual Assistant Market - Global Industry Analysis, Size, Share, Growth, Trends and Forecast 2013 - 2019. LON-REPORTBUYER.

  • O'Sullivan S, Nevejans N, Allen C, Blyth A, Leonard S, Pagallo U, Holzinger K, Holzinger A, Sajid MI, Ashrafian H (2019) Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery. Int J Med Robot Comput Assisted Surg 15(1). https://doi.org/10.1002/rcs.1968

  • Panigrahi SK, Kar FW, Fen TA, Hoe LK, Wong M (2018) A strategic initiative for successful reverse logistics management in retail industry. Glob Bus Rev 19(3_suppl). https://doi.org/10.1177/0972150918758096

  • Peng CGY, Alber M, Tepole AB, Cannon WR, De S, Dura-Bernal S, Garikipati K, Karniadakis G, Lytton WW, Perdikaris P, Petzold L, Kuhl E (2021) Multiscale modeling meets machine learning: What can we learn? Arch Comput Methods Eng 28(3):1017–1037.https://doi.org/10.1007/s11831-020-09405-5

    Article  MathSciNet  Google Scholar 

  • Phadke S (2021) FinTech future: the digital DNA of finance.https://doi.org/10.4135/9789353885687

  • Pugalenthi R, Prabhu Chakkaravarthy A, Ramya J, Babu S, Rasika Krishnan R (2021) Artificial learning companion using machine learning and natural language processing. Int J Speech Technol 24(3). https://doi.org/10.1007/s10772-020-09773-0

  • Ramaswamy S, DeClerck N (2018) Customer perception analysis using deep learning and NLP. In: Procedia Computer Science, vol 140. https://doi.org/10.1016/j.procs.2018.10.326

  • Redondo R, Herrero Á, Corchado E, Sedano J (2020) A decision-making tool based on exploratory visualization for the automotive industry. Appl Sci (Switzerland) 10(12). https://doi.org/10.3390/app10124355

  • Santosh Kumar J, Raghavendra BK, Raghavendra S, Meenakshi M (2020) Performance evaluation of Map-reduce jar pig hive and spark with machine learning using big data. Int J Electr Comput Eng 10(4). https://doi.org/10.11591/ijece.v10i4.pp3811-3818

  • Straker K, Wrigley C (2016) Emotionally engaging customers in the digital age: the case study of ‘Burberry love. J Fashion Market Manage 20(3). https://doi.org/10.1108/JFMM-10-2015-0077

  • Times E (2020) Intelligent IoT: bringing the power of AI to the Internet of Things. ELE Times

  • Trunk A, Birkel H, Hartmann E (2020) On the current state of combining human and artificial intelligence for strategic organizational decision making. Bus Res. 13(3). https://doi.org/10.1007/s40685-020-00133-x

Download references

Funding

The study is not from any institutional research project. So no relevant funding information.

Author information

Authors and Affiliations

  1. School of Accounting, Jiujiang University, 551 Qianjin Donglu, Jiujiang, Jiangxi, China

    Alim Al Ayub Ahmed

  2. Department of Business Studies, European International College, Abu Dhabi, United Arab Emirates

    Sugandha Agarwal

  3. Faculty of Economics, Management, Universitas Teknologi Yogyakarta, Yogyakarta, Indonesia

    IMade Gede Ariestova Kurniawan

  4. International Univ Liaison Indonesia, BSD City, Serpong, Tangerang, Indonesia

    Samuel P. D. Anantadjaya

  5. Amity International Business School, Amity University, Noida, India

    Chitra Krishnan

Authors
  1. Alim Al Ayub Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sugandha Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. IMade Gede Ariestova Kurniawan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Samuel P. D. Anantadjaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chitra Krishnan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alim Al Ayub Ahmed.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest and all ethical issues including human or animal participation has been done. No such consent is applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ahmed, A.A.A., Agarwal, S., Kurniawan, I.G.A. et al. Business boosting through sentiment analysis using Artificial Intelligence approach. Int J Syst Assur Eng Manag 13 (Suppl 1), 699–709 (2022). https://doi.org/10.1007/s13198-021-01594-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-021-01594-x

Keywords

Search

Navigation