Related papers: Experiments on Data Preprocessing of Persian Blog …
Social media has been remarkably grown during the past few years. Nowadays, posting messages on social media websites has become one of the most popular Internet activities. The vast amount of user-generated content has made social media…
Introduction: Microblogging websites have massed rich data sources for sentiment analysis and opinion mining. In this regard, sentiment classification has frequently proven inefficient because microblog posts typically lack syntactically…
Social media hold valuable, vast and unstructured information on public opinion that can be utilized to improve products and services. The automatic analysis of such data, however, requires a deep understanding of natural language. Current…
The rapid growth in data on the internet requires a data mining process to reach a decision to support insight. The Persian language has strong potential for deep research in any aspect of natural language processing, especially sentimental…
Sentiment analysis aims to extract people's emotions and opinion from their comments on the web. It widely used in businesses to detect sentiment in social data, gauge brand reputation, and understand customers. Most of articles in this…
The rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and…
The large amounts of data continuously generated online offer opportunities to identify and analyse trends in various aspects of society. For instance, data from online social media are frequently used as a means of analysing informal…
This paper introduces the hmBlogs corpus for Persian, as a low resource language. This corpus has been prepared based on a collection of nearly 20 million blog posts over a period of about 15 years from a space of Persian blogs and includes…
Recently, there has been a growing interest in the use of deep learning techniques for tasks in natural language processing (NLP), with sentiment analysis being one of the most challenging areas, particularly in the Persian language. The…
Text mining is becoming vital as Web 2.0 offers collaborative content creation and sharing. Now Researchers have growing interest in text mining methods for discovering knowledge. Text mining researchers come from variety of areas like:…
Today, Social networks such as Twitter are the most widely used platforms for communication of people. Analyzing this data has useful information to recognize the opinion of people in tweets. Sentiment analysis plays a vital role in NLP,…
Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive…
One of the new scientific ways of understanding discourse dynamics is analyzing the public data of social networks. This research's aim is Post-structuralist Discourse Analysis (PDA) of Covid-19 phenomenon (inspired by Laclau and Mouffe's…
World Wide Web is a huge repository of web pages and links. It provides abundance of information for the Internet users. The growth of web is tremendous as approximately one million pages are added daily. Users' accesses are recorded in web…
Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In…
The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject's sentiment (e.g., positive, negative, or neutral) towards a…
Blogs are the recent emerging media which relies on information technology and technological advance. Since the mass media in some less-developed and developing countries are in government service and their policies are developed based on…
Sentiment analysis attempts to identify, extract and quantify affective states and subjective information from various types of data such as text, audio, and video. Many approaches have been proposed to extract the sentiment of individuals…
We introduce FaBERT, a Persian BERT-base model pre-trained on the HmBlogs corpus, encompassing both informal and formal Persian texts. FaBERT is designed to excel in traditional Natural Language Understanding (NLU) tasks, addressing the…
The social media network phenomenon leads to a massive amount of valuable data that is available online and easy to access. Many users share images, videos, comments, reviews, news and opinions on different social networks sites, with…