相关论文: A Survey of Data Mining Techniques for Social Medi…

Nowadays, the interest given by the scientific community to the investigation of the data generated by social networks is increasing as much as the exponential increasing of social network data. The data structure complexity is one among…

The modern age has seen an exponential growth of social network data available on the web. Analysis of these networks reveal important structural information about these networks in particular and about our societies in general. More often…

Networks have attracted a burst of attention in the last decade, with applications to natural, social, and technological systems. While networks provide a powerful abstraction for investigating relationships and interactions, the…

Social networks have become a part in the daily life of millions of users, which offer wide range of interests and practices. The main characteristic of social networks is its ability to gather different individuals around a common point of…

Data Mining is the process of examining the information from different point of view and compressing it for the relevant data. This data can also be utilized to build the incomes. Data Mining is also known as Data or Knowledge Discovery.…

In this paper we have focused a variety of techniques, approaches and different areas of the research which are helpful and marked as the important field of data mining Technologies. As we are aware that many Multinational companies and…

Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Sequential pattern mining…

Data mining is the task of discovering interesting, unexpected or valuable structures in large datasets and transforming them into an understandable structure for further use . Different approaches in the domain of data mining have been…

The broad adoption of online social networking platforms has made it possible to study communication networks at an unprecedented scale. Digital trace data can be compiled into large data sets of online discourse. However, it is a challenge…

Social media platforms like Twitter, Facebook, and Instagram have facilitated the spread of misinformation, necessitating automated detection systems. This systematic review evaluates 36 studies that apply machine learning (ML) and deep…

An important part of the information gathering and data analysis is to find out what people think about, either a product or an entity. Twitter is an opinion rich social networking site. The posts or tweets from this data can be used for…

The amount of text that is generated every day is increasing dramatically. This tremendous volume of mostly unstructured text cannot be simply processed and perceived by computers. Therefore, efficient and effective techniques and…

Among the vast information available on the web, social media streams capture what people currently pay attention to and how they feel about certain topics. Awareness of such trending topics plays a crucial role in multimedia systems such…

Twitter stream has become a large source of information for many people, but the magnitude of tweets and the noisy nature of its content have made harvesting the knowledge from Twitter a challenging task for researchers for a long time.…

The digital revolution has led to the digitization of human behavior, creating unprecedented opportunities to understand observable actions on an unmatched scale. Emerging phenomena such as crowdfunding and crowdsourcing have further…

Over the past decade humans have experienced exponential growth in the use of online resources, in particular social media and microblogging websites such as Facebook, Twitter, YouTube and also mobile applications such as WhatsApp, Line,…

Social Network Mining (SNM) has become one of the main themes in big data agenda. As a resultant network, we can extract social network from different sources of information, but the information sources were growing dynamically require a…

Cluster analysis is a field of data analysis that extracts underlying patterns in data. One application of cluster analysis is in text-mining, the analysis of large collections of text to find similarities between documents. We used a…

Micro-blogging service Twitter is a lucrative source for data mining applications on global sentiment. But due to the omnifariousness of the subjects mentioned in each data item; it is inefficient to run a data mining algorithm on the raw…

In recent years, social networks have shown diversity in function and applications. People begin to use multiple online social networks simultaneously for different demands. The ability to uncover a user's latent topic and social network…