Can artificial intelligence help improve sentiment analysis of changes in Internet user awareness conducted using Big Data Analytics as relevant additional market research conducted on large amounts of data and information extracted from the pages of many online social media users?
In recent years, more and more companies and enterprises, before launching new product and service offerings as part of their market research, commission sentiment analysis of changes in public sentiment, changes in awareness of the company's brand, recognition of the company's mission and awareness of its offerings to specialized marketing research firms. This kind of sentiment analysis is carried out on computerized Big Data Analytics platforms, where a multi-criteria analytical process is carried out on a large set of data and information taken from multiple websites. In terms of source websites from which data is taken, information is dominated by news portals that publish news and journalistic articles on a specific issue, including the company, enterprise or institution commissioning this type of study. In addition to this, the key sources of online data include the pages of online forums and social media, where Internet users conduct discussions on various topics, including product and service offers of various companies, enterprises, financial or public institutions. In connection with the growing scale of e-commerce, including the sale of various types of products and services on the websites of online stores, online shopping portals, etc., as well as the growing importance of online advertising campaigns and promotional actions carried out on the Internet, the importance of the aforementioned analyses of Internet users' sentiment on specific topics is also growing, as playing a complementary role to other, more traditionally conducted market research. A key problem for this type of sentiment analysis is becoming the rapidly growing volume of data and information contained in posts, comments, posts, banners and advertising spots posted on social media, as well as the constantly emerging new social media. This problem is partly solved by the issue of increasing computing power and multi-criteria processing of large amounts of data thanks to the use of increasingly improved microprocessors and Big Data Analytics platforms. In addition, in recent times, the possibilities of advanced multi-criteria processing of large sets of data and information in increasingly shorter timeframes may significantly increase when generative artificial intelligence technology is involved in the aforementioned data processing.
The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:
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I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:
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In view of the above, I address the following question to the esteemed community of scientists and researchers:
Can artificial intelligence help improve sentiment analysis of changes in Internet users' awareness conducted using Big Data Analytics as relevant additional market research conducted on a large amount of data and information extracted from the pages of many online social media users?
Can artificial intelligence help improve sentiment analysis conducted on large data sets and information on Big Data Analytics platforms?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
Certainly, artificial intelligence (AI) holds significant promise in enhancing sentiment analysis on large datasets within Big Data Analytics platforms. By leveraging advanced machine learning algorithms, AI can efficiently process vast amounts of textual data to extract nuanced insights about sentiments expressed by users. AI algorithms can detect patterns, sentiments, and emotions in text data with a high degree of accuracy, allowing organizations to gain deeper understanding and actionable insights from their data.
Moreover, AI-powered sentiment analysis can adapt and evolve by continuously learning from new data. This adaptive nature enables AI models to improve their accuracy and relevance over time, ensuring that sentiment analysis remains effective even as data volumes and complexity increase.
Furthermore, AI can handle various forms of unstructured data, including text, images, and videos, enabling comprehensive sentiment analysis across multiple data sources. This holistic approach allows organizations to gain a more comprehensive understanding of customer opinions, market trends, and brand sentiment.
In summary, AI has the potential to revolutionize sentiment analysis by offering scalable, accurate, and adaptive solutions that can unlock valuable insights from large datasets within Big Data Analytics platforms.
In my opinion, yes, artificial intelligence (AI) can indeed play a crucial role in improving sentiment analysis for changes in internet user awareness, especially when combined with big data analytics. Here's how:
Thank You
Dariusz Prokopowicz
In the realm of Big Data Analytics, AI helps in efficiently processing and extracting insights from massive datasets. AI-powered sentiment analysis can handle the volume, velocity, and variety of data found in these platforms. The models can adapt and learn from new data, improving over time, and allowing for more precise sentiment classification on diverse and dynamic datasets.
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