دانلود و نمایش مقالات مرتبط با sentiment analysis::صفحه 1
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نتیجه جستجو - sentiment analysis

تعداد مقالات یافته شده: 33
ردیف عنوان نوع
1 Mapping the political landscape of Persian Twitter: The case of 2013 presidential election
نقشه چشم انداز سیاسی توییتر فارسی: مورد انتخابات ریاست جمهوری سال 2013-2019
The fallacy of premature designations such as ‘‘Iran’s Twitter Revolution’’ can be attributed to the empirical gap in our knowledge about such sociotechnical phenomena in non-Western societies. To fill this gap, we need in-depth analyses of social media use in those contexts and to create detailed maps of online public environments in such societies. This paper aims to present such cartography of the political landscape of Persian Twitter by studying the case of Iran’s 2013 presidential election. The objective of this study is twofold: first, to fill the empirical gap in our knowledge about Twitter use in Iran, and second, to develop computational methods for studying Persian Twitter (e.g., effective methods for analyzing Persian text) and identify the best methods for addressing different issues (e.g., topic detection and sentiment analysis). During Iran’s 2013 presidential election, three million tweets were collected and analyzed using social network analysis and machine learning. The findings provide a more nuanced view of the political landscape of Persian Twitter and identify patterns in accordance with or in contrast to those identified in the English-speaking Twittersphere around the 2013 presidential election. Persian Twitter was dominated by micro-celebrities, whereas institutional elites dominated English discourse about Iran on Twitter. The results also illustrate that Persian Twitter in 2013 was predominantly in favor of reformists. Finally, this study demonstrates that sentiment analysis toward political name entities can be used efficiently for mapping the political landscape of conversation on Twitter.
Keywords: Twitter | Iran | social network analysis | political landscape | computational methods | Big Data
مقاله انگلیسی
2 تحلیل احساسات مبتنی بر یادگیری عمیق در متن رومی اردو
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 5 - تعداد صفحات فایل doc فارسی: 9
آنالیز احساسات با توجه به رویکرد همه جانبه در آنالیز احساسات کاربران شبکه های اجتماعی مختلف، انجمن ها، سایت های بازاریابی الکترونیکی و وبلاگ ها، اهمیت زیادی دارد. داده های مربوط به احساسات در وب اهمیت زیادی دارد و بر مشتریان، خوانندگان و شرکت های تجاری تأثیر می گذارد. شبکه عصبی مکرر به طور گسترده ای در انجام وظایف پردازش زبان طبیعی مورد استفاده قرار گرفته است، زیرا برای مدل سازی داده های متوالی به صورت موثر طراحی شده است.
در این مقاله از مدل عصبی عمیق حافظه کوتاه-طولانی مدت (LSTM) استفاده شده است. توانایی فوق العاده ای در ضبط اطلاعات دور برد و حل مشکل کاهش گرادیان و همچنین ارائه اطلاعات متنی آتی، معناشناسی توالی لغات با شکوه دارد. این مقاله پایه و اساس تطبیق روش های یادگیری عمیق در آنالیز رومن اردو است. نتایج تجربی نشان داد که مدل ما دقت قابل توجهی دارد و دقت بیشتری از روش های یادگیری ماشین دارد.
کليدواژه: شبکه عصبی مکرر (RNN)| حافظه کوتاه-بلند مدت (LSTM) | آنالیز معنایی رومن اردو | تعبیه لغت
مقاله ترجمه شده
3 Assessing learners satisfaction in collaborative online courses through a big data approach
ارزیابی رضایتمندی دانشجویان در دوره های آنلاین همکاری از طریق رویکرد داده ای بزرگ-2018
Monitoring learners satisfaction (LS) is a vital action for collecting precious information and design valuable online collaborative learning (CL) experiences. Todays CL platforms allow students for per forming many online activities, thus generating a huge mass of data that can be processed to provide insights about the level of satisfaction on contents, services, community interactions, and effort. Big Data is a suitable paradigm for real-time processing of large data sets concerning the LS, in the final aim to provide valuable information that may improve the CL experience. Besides, the adoption of Big Data offers the opportunity to implement a non-intrusive and in-process evaluation strategy of online courses that complements the traditional and time-consuming ways to collect feedback (e.g. questionnaires or surveys). Although the application of Big Data in the CL domain is a recent explored research area with limited applications, it may have an important role in the future of online education. By adopting the design science research methodology, this article describes a novel method and approach to analyse individual students contributions in online learning activities and assess the level of their satisfaction towards the course. A software artefact is also presented, which leverages Learning Analytics in a Big Data context, with the goal to provide in real-time valuable insights that people and systems can use to intervene properly in the program. The contribution of this paper can be of value for both researchers and practitioners: the former can be interested in the approach and method used for LS assessment; the latter can find of interest the system implemented and how it has been tested in a real online course.
Keywords: Big data ، Clustering ، Collaborative learning ، Learning analytics ، Learning satisfaction ، Sentiment analysis
مقاله انگلیسی
4 معیارهای رسانه های اجتماعی و تحلیل احساسات برای ارزیابی اثربخشی پست های رسانه های اجتماعی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 14
پژوهش حاضر معیارهای برای موفقیت در خودبازاریابی برای رسانه های اجتماعی ارائه می دهد. شرکت کنندگان شامل گیمرهای یوتیوب بودند. ما بر روی محتوای ارتباطات شان در فیس بوک تمرکز می کنیم تا تفاوت های قابل توجهی ملاک ها و تفسیر احساسات فیس بوک شان را شناسایی کنیم. در این راستا روش تحقيقANOVA و تحليل احساسات مورد استفاده قرار گرفت. تجزیه و تحلیل دسته بندی شده ی پست طبقه بندی شده ANOVA نشان داد که فیلم های یوتیوب لایک ها ، کامنت ها و اشتراک های کم اهمیتر را به دست آورد. از سوی دیگر به عکس ها در مقایسه با سایر انواع نمونه پست ها، تمایل بیشتری نشان دادند. تجزیه و تحلیل احساسات نشان می دهد که منفی بودن احساس فالورها، زمانی بود که فعالیت های تولید شده توسط کاربر نسبتا کم بود. این مسئله نتایج مکمل ارزشمندی را برای تجزیه و تحلیل سایر شاخص های پست مانند تعداد لایک ها، کامنت ها و اشتراک ها فراهم کرد. نتایج پژوهش ضرورت استفاده از تکنیک های پردازش زبان طبیعی برای بهینه سازی برند ارتباطات در مورد رسانه های اجتماعی و اهمیت بررسی نظر توده ها برای درک بهتر بازخورد مصرف کنندگان را نشان داد.
کلمات کلیدی: معیارهای رسانه اجتماعی | خود بازاریابی | تجزیه و تحلیل احساسات
مقاله ترجمه شده
5 A view of Occupy Central impacts on Hong Kong tourism from the other side of the Great Firewall: A rejoinder to Luo & Zhai
یک نگاهی به تاثیرات مرکزی شغل روی گردشگری هنگ کنگ از بخش دیگر دیواره آتش بزرگ: یک جوابیه به لو و ژای-2018
This paper forms a rejoinder to the paper by Luo & Zhai (‘“I will never go to Hong Kong again!” How the secondary crisis communication of “Occupy Central” on Weibo shifted to a tourism boycott’). It discusses claims Luo and Zhai (2017) make about negative impacts of Occupy Central protests on tourism sector in Hong Kong and debates application of sentiment analysis to censored social media platforms. The rejoinder concludes that there is no clear evidence that there has been a negative impact of Occupy Central on Hong Kong tourism. It also urges tourism academics to be more critical regarding the sources of information for their studies.
keywords: Hong Kong |Political crisis |Social media |Tourism impacts
مقاله انگلیسی
6 Combining different evaluation systems on social media for measuring user satisfaction
ترکیب سیستم های مختلف ارزیابی در رسانه های اجتماعی برای اندازه گیری رضایت کاربر-2018
Web 2.0 allows people to express and share their opinions about products and services they buy/ use. These opinions can be expressed in various ways: numbers, texts, emoticons, pictures, vi deos, audios, and so on. There has been great interest in the strategies for extracting, organising and analysing this kind of information. In a social media mining framework, in particular, the use of textual data has been explored in depth and still represents a challenge. On a rating and review website, user satisfaction can be detected both from a rating scale and from the written text. However, in common practice, there is a lack of algorithms able to combine judgments provided with both comments and scores. In this paper we propose a strategy to jointly measure the user evaluations obtained from the two systems. Text polarity is detected with a sentiment-based approach, and then combined with the associated rating score. The new rating scale has a finer granularity. Moreover, also enables the reviews to be ranked. We show the effectiveness of our proposal by analysing a set of reviews about the Uffizi Gallery in Florence (Italy) published on TripAdvisor.
Keywords: Social media ، Sentiment analysis ، Rating ، Knowledge management
مقاله انگلیسی
7 Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges
استخراج ضمنی جنبه در تحلیل احساسات: مرور، طبقه بندی، فرصت ها و چالش های باز-2018
Sentiment analysis is a text classification branch, which is defined as the process of extracting sentiment terms (i.e. feature/aspect, or opinion) and determining their opinion semantic orientation. At aspect level, aspect extraction is the core task for sentiment analysis which can either be implicit or explicit aspects. The growth of sentiment analysis has resulted in the emergence of various techniques for both explicit and implicit aspect extraction. However, majority of the research attempts targeted explicit aspect extraction, which indicates that there is a lack of research on implicit aspect extraction. This research provides a review of implicit aspect/features extraction techniques from different perspectives. The first perspective is making a comparison analysis for the techniques available for implicit term extraction with a brief summary of each technique. The second perspective is classifying and comparing the performance, datasets, language used, and shortcomings of the available techniques. In this study, over 50 articles have been reviewed, however, only 45 articles on implicit aspect extraction that span from 2005 to 2016 were analyzed and discussed. Majority of the researchers on implicit aspects extraction rely heavily on unsupervised methods in their research, which makes about 64% of the 45 articles, followed by supervised methods of about 27%, and lastly semi-supervised of 9%. In addition, 25 articles conducted the research work solely on product reviews, and 5 articles conducted their research work using product reviews jointly with other types of data, which makes product review datasets the most frequently used data type compared to other types. Furthermore, research on implicit aspect features extraction has focused on English and Chinese languages compared to other languages. Finally, this review also provides recommendations for future research directions and open problems.
keywords: Aspect extraction| Implicit aspect| Implicit feature| Sentiment analysis| Sentiment extraction
مقاله انگلیسی
8 Combining different evaluation systems on social media for measuring user satisfaction
ترکیب کردن سیستمهای مختلف ارزیابی روی رسانه های اجتماعی برای سنجش رضایت کاربر-2018
Web 2.0 allows people to express and share their opinions about products and services they buy/use. These opinions can be expressed in various ways: numbers, texts, emoticons, pictures, videos, audios, and so on. There has been great interest in the strategies for extracting, organising and analysing this kind of information. In a social media mining framework, in particular, the use of textual data has been explored in depth and still represents a challenge. On a rating and review website, user satisfaction can be detected both from a rating scale and from the written text. However, in common practice, there is a lack of algorithms able to combine judgments provided with both comments and scores. In this paper we propose a strategy to jointly measure the user evaluations obtained from the two systems. Text polarity is detected with a sentiment-based approach, and then combined with the associated rating score. The new rating scale has a finer granularity. Moreover, also enables the reviews to be ranked. We show the effectiveness of our proposal by analysing a set of reviews about the Uffizi Gallery in Florence (Italy) published on TripAdvisor.
keywords: Social media| Sentiment analysis| Rating|Knowledge management
مقاله انگلیسی
9 Impact of product attributes on customer satisfaction: An analysis of online reviews for washing machines
تاثیر ویژگی های محصول روی رضایت مشتری: یک تحلیل روی بازدیدهای آنلاین برای ماشین های لباسشویی-2018
Online reviews are an important information source for companies analysing users’ demands. We conducted a study of online reviews to measure how product attributes impact customer satisfaction. First, we attempted to infer through sentiment analysis whether a customer is satisfied with a purchase according to their review. Second, a logistic regression model was developed to estimate the impact of various product properties on customer satisfaction scores. Our estimates indicated that customer satisfaction is influenced by drainage mode, loading type, frequency conversion, type, display, colour, and capacity. We further investigate the impact of price and find that customers who buy cheap products should be treated differently from purchasers of expensive items because the relevance of design features on their satisfaction is different. Additionally, we observed that although customers are concerned about noise, perceived noise is not consistent with actual noise levels. We analysed specific reviews and then obtained more detailed information on customer attitudes.
keywords: Customer behavior |Customer satisfaction |Online reviews |Product attributes |Product design
مقاله انگلیسی
10 The secondary crisis communication of Occupy Central on Weibo: A response to Denis Tolkach
ارتباط بحران ثانویه اشغال مرکزی در Weibo: پاسخ به دنیس تولکچ-2018
This is a response to the rejoinder by Tolkach (2018) to Luo and Zhais (2017) paper (“I will never go to Hong Kong again” How the secondary crisis communication of “Occupy Central” on Weibo shifted to a tourism boycott). The authors recognize Tolkachs suggestion on academic debates but hold different opinions to his arguments. Thus, further clarification is provided to Tolkachs two main concerns: the impact of Occupy Central on Hong Kong tourism and sentiment analysis of censored material. This response emphasizes that Luo and Zhai primarily discussed the secondary crisis communication and public emotions that arose in the Chinese social media over the events in Hong Kong, and not the events themselves. Additionally this rejoinder provides more information on Tourism between mainland China and Hong Kong, the environment of Chinese social media, and academic research progress in mainland China. It also advocates an “empathetic understanding” in cross-cultural academic dialogue.
Keywords: Secondary crisis communication ، Social media ، Emotions ، Tourism boycott ، Rejoinder
مقاله انگلیسی
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