ارائه روشی برای تحلیل نظرهای کاربران رسانه اجتماعی توییتر به‌منظور نوآوری در مدل کسب‌‌وکار

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشیار، گروه مهندسی فناوری اطلاعات، دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران
2 دانشجوی کارشناسی ارشد، مهندسی فناوری اطلاعات، دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران
10.22034/aimj.2023.197450
چکیده
در عصر حاضر، با توجه به گسترش روزافزون اینترنت، داده‌های متنی عظیم با سرعت زیاد تولید می‌شوند. در تجارت الکترونیک کلمات عضو جدانشدنی تعاملات خریدوفروش هستند. نظرهای آنلاین، اخبار، ارتباطات بازاریابی و دیگر تعاملات و همچنین، دیجیتالی شدن اطلاعات، مقدار زیادی داده متنی ایجاد می‌کنند که کسب‌وکارها تمایل به استفاده از آن‌ها دارند. داده‌های متنی توسط افراد، شرکت‌ها و جوامع ایجاد می‌شود. در گذشته محققان و کسب‌وکارها، برای کسب بینش درباره مشتریان خود، از روش‌های دستی استفاده می‌کردند که این روش‌ها به نیروی انسانی، هزینه مالی و زمان پردازش زیادی نیاز داشت و به‏علت دخالت انسان در تحلیل، این روش‌ها در مقابل سوگیری‌های تحلیل‌کننده و پاسخ‌دهنده ضعیف بودند. با استفاده از متن‌کاوی می‌توانیم اطلاعات موردنیاز برای شرکت‌ها را به‌صورت خودکار، با هزینه کم و به‌روز تحلیل کنیم تا شرکت‌ها بتوانند از آن در نوآوری مدل کسب‌وکار استفاده کنند. در این پژوهش توییت‌های مشتریان به پشتیبانی کمپانی اپل و پاسخ‌های آن‌ها به‌کمک روش‌های تحلیل احساس و روش انتساب نهفته دیریکله بررسی ‌شده است. همچنین روش پیشنهادی ترکیبی جدیدی، بر اساس نتایج این دو روش برای دستیابی به بینش عمیق‌تر درباره داده‌ها ارائه‌ شده و از نتایج به‌دست‌آمده، راه‏کارهایی برای بهبود مدل کسب‌وکار شرکت اپل پیشنهاد شده است.

کلیدواژه‌ها


عنوان مقاله English

Proposing A Method For Analyzing User Comments On Twitter Social Media Platform For Business Model Innovation

نویسندگان English

Monireh Hosseini 1
Tina Akhlaghi Meskin 2
1 Associate Prof., Department of Information Technology Engineering, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 MSc. Student, Department of Information Technology Engineering ,Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
چکیده English

In our current era, with the advancements in the use of Internet, a large amount of textual data is being rapidly created. Words are an inseparable part of online transactions in E-commerce. Online comments, news, marketing and other types of communication along with the digitalization of data creates a huge amount of textual data that businesses would like to use. Textual data gets created by people, organizations and communities. In the past, researchers and businesses employed manual methods to gain insights about their customers, which required significant human effort, financial resources, and processing time. Due to human intervention in analysis, these methods were susceptible to analyst and respondent biases. By using text mining we can analyze the necessary information for companies in an automatic and cost-effective way in real time, enabling the use of the results for business model innovation. This research examines customer tweets directed at the Apple company and the company's responses using sentiment analysis methods and Latent Dirichlet Allocation. Furthermore, a new method has been suggested to combine the results of these two methods in order to gain deeper insights into the data and use the results to give recommendations for enhancing Apple company’s business model.

کلیدواژه‌ها English

Text mining
Automatic Text Analysis
Data Analysis
Business Model Innovation
Latent Dirichlet Allocation
Sentiment Analysis
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  • تاریخ دریافت 09 شهریور 1402
  • تاریخ بازنگری 12 اسفند 1402
  • تاریخ پذیرش 30 اردیبهشت 1403