Online social media systems (such as YouTube or Reddit) provide commenting features to support augmentation of social objects (e.g. video clips or news articles). Unfortunately, many comments are not useful due to the varying intentions of the authors of comments as well as the perspectives of the readers. In this paper, we present, a framework and Web-based system for adaptive faceted ranking ...

The development of information technology is increasingly rapid, such as social media, which has much influence. Social media a place or used to express and various opinions on topic. One example Instagram. Instagram platform with many features, posting photos, videos, comments, likes, others. comments feature that contained public opinion can be data. Nothing but the post SMB Telkom University...

Unsolicited or unwanted messages is a byproduct of virtually every popular social media website. Spammers have become increasingly proficient at bypassing conventional spam filters, prompting a stronger effort to develop new methods that accurately detect spam while simultaneously acting as a more robust classifier against users that modify their behavior in order to avoid detection. This paper...

This study investigates the influences of prosocial and antisocial tendency Weibo users on post transmission during COVID-19 pandemic. To overcome deficiency existing research emotions, we employ a web crawler technology to obtain data from identify texts with or emotions. We use SnowNLP construct semantic dictionaries training models. Our major findings include following. First, through correl...

In this paper we present an approach for diversifying user comments on news articles. In our proposed framework, we analyse user comments w.r.t. four different criteria in order to extract the respective diversification dimensions in the form of feature vectors. These criteria involve content similarity, sentiment expressed within comments, article’s named entities also found within comments an...

In this paper we developed and tested a new algorithm of detecting in social networks users (so-called trolls) who behave in an insulting and provocative way towards other users. In order to detect trolls it is proposed to unite users in groups where all the members have a similar way of communicating. Defining the number of group and distributing the users into these groups is carried out auto...

With vast amounts of data being created on location-based social networks (LBSNs) such as Yelp and Foursquare, making effective personalised suggestions to users is an essential functionality. Matrix Factorisation (MF) is a collaborative filtering-based approach that is widely used to generate suggestions relevant to user’s preferences. In this paper, we address the problem of predicting the ra...

The world engaged in online sport watching during COVID-19. Fortunately, Taiwan, the pandemic was stably controlled 2020, allowing for continuation of Chinese Professional Baseball League (CPBL); this attracted international attention and encouraged relevant discussions on social media Taiwan. In present study, through text mining, we analyzed user content (e.g., concepts sports service quality...