Microblog Emotion Analysis Using Improved DBN Under Spark Platform
نویسندگان
چکیده
In order to solve the problems that traditional single-machine methods find it difficult complete task of emotion classification quickly, and time efficiency scalability are not high; a microblog analysis method using improved deep belief network (DBN) under Spark platform is proposed. First, Hadoop distributed file system used realize storage text data, preprocessed data dictionary converted into word vector representation based on continuous bag-of-words model. Then, an DBN model constructed by combining adaptive learning with active method, applied vectors. Finally, parallel optimization realized, accurately quickly obtain types texts. The experimental proposed set shows accuracy more than 94%.
منابع مشابه
Emotion Analysis Platform on Chinese Microblog
Weibo, as the largest social media service in China, has billions of messages generated every day. The huge number of messages contain rich sentimental information. In order to analyze the emotional changes in accordance with time and space, this paper presents an Emotion Analysis Platform (EAP), which explores the emotional distribution of each province, so that can monitor the global pulse of...
متن کاملDBN-ivector Framework for Acoustic Emotion Recognition
Deep learning and i-vectors have been successfully used in speech and speaker recognition recently. In this work we propose a framework based on deep belief network (DBN) and ivector space modeling for acoustic emotion recognition. We use two types of labels for frame level DBN training. The first one is the vector of posterior probabilities calculated from the GMM universal background model (U...
متن کاملEmotion Modeling from Writer/Reader Perspectives Using a Microblog Dataset
Most recent studies on emotion analysis and detection focus on how writers express their emotions through textual information. In this paper, we model emotion generation on the Plurk microblogging platform from both writer and reader perspectives. Support Vector Machine (SVM)-based classifiers are used for emotion prediction. To better model emotion generation on such a social network, three ty...
متن کاملEmotion Classification in Microblog Texts Using Class Sequential Rules
This paper studies the problem of emotion classification in microblog texts. Given a microblog text which consists of several sentences, we classify its emotion as anger, disgust, fear, happiness, like, sadness or surprise if available. Existing methods can be categorized as lexicon based methods or machine learning based methods. However, due to some intrinsic characteristics of the microblog ...
متن کاملPredicting Emotion Labels for Chinese Microblog Texts
We describe an experiment into detecting emotions in texts on the Chinese microblog service Sina Weibo (www.weibo.com) using distant supervision via various author-supplied emotion labels (emoticons and smilies). Existing word segmentation tools proved unreliable; better accuracy was achieved using characterbased features. Higher-order n-grams proved to be useful features. Accuracy varied accor...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Information Technologies and Systems Approach
سال: 2023
ISSN: ['1935-570X', '1935-5718']
DOI: https://doi.org/10.4018/ijitsa.318141