A Survey on Uncovering trending stories from Twitter by extracting ground truth from datasets

Today’s online social networking services generates series of conversation that shows the all kinds of real-world events, however the large amount of data are available on social network. This data can be filtered for finding trending topics using standard natural language processing techniques. An Uncovering trending stories is therefore a building block is to extract and summarizes the information raised from social networking services, this building block is very useful to find trending stories and its initiator .There are verity of methods that improves quality of result. This paper explores about different Topic detection method for uncovering trending topics from twitter datasets, such as Document-Pivot methods, Feature-Pivot methods, Frequent Pattern Mining, Soft Frequent Pattern Mining and BNgram

Uncovering Trending Stories from Twitter by Extracting Ground Truth from Datasets

Social networking services like Twitter generates contents that reflects series of conversation which shows real-world events. Twitter is social networking site that provide service for a large number of users to communicate with each other simultaneously; it is an asymmetrical relationship between friends and followers that provides an interesting structure among the users of Twitter. Twitter’s series of messages called tweets, which are restricted to 140 characters and thus are usually much focused. The basic process is to capture tweets from twitter that extract mostly discussed topic in between users. This tweet dataset can be process for finding trending stories using standard natural language processing. An Uncovering trending stories is therefore a building block is to extract and summarizes the information raised from social networking services. There is verity of methods for finding trending stories that improves quality of result. This paper proposes application for uncovering trending topics from twitter datasets using BNgram topic detection method. DOI: 10.17762/ijritcc2321-8169.15069

#Trending: a reevaluation of traditional news values given twitter through a mixed methods approach

Over the years, social media have catered for faster and perhaps more efficient delivery of news. Twitter, one of the most popular micro-blogging sites, is now being used by journalists in spreading and gathering news. And since Twitter takes note of what topics are trending, journalists now have an idea on what their audience would like to know and talk about. However, topics trending on Twitter often do not reflect the dominant news values presented by the journalists in the traditional news media, thus creating a gap between the perceptions of the audience and of the journalist on what are considered to be newsworthy especially on Twitter. This also creates an impression that news and news values are evolving. This exploratory mixed methods research re-evaluates the traditional news values in the age of Twitter. It seeks to determine if such values have evolved and if they remain relevant for journalists in the delivery of news in this entirely new platform. Four news values were identified given a phenomenological approach employed in qualitative interviews. These identified news values were then tested using a survey (N=300) as structural equation modelling was employed to test if these four news values are correlated to newsworthiness, news consumption and news distribution. It was found that the traditional news values relevant in journalists' practice of news judgment and in audience' interaction on Twitter. This study contributes to discourses on news values which are currently being reviewed given how the Internet and social media have influenced journalism

#Trending: A reevaluation of traditional news values given Twitter through a mixed methods approach

Over the years, social media has catered for faster and perhaps more efficient delivery of news. Twitter, one of the most popular micro-blogging sites, is now being used by journalists in spreading and gathering news. And since Twitter takes note of what topics are trending, journalists now have an idea on what their audience would like to know and talk about. However, topics trending on Twitter often do not reflect the dominant news values presented by the journalists in the traditional news media, thus creating a gap between the perceptions of the audience and of the journalist on what are considered to be newsworthy especially on Twitter. This also creates an impression that news and the news values are evolving. This exploratory mixed methods research re-evaluates the traditional news values in the age of Twitter. It seeks to determine if such values have evolved and if they remain relevant for journalists in the delivery of news in this entirely new platform. Four news values were identified given a phenomenological approach employed in qualitative interviews. These identified news values were then tested using a survey (N=300) as structural equation modeling was employed to test if these four news values are correlated to newsworthiness, news consumption and news distribution. This study contributes to discourses on news values which are currently being reviewed given how the Internet and social media have influenced journalism.Venice Nicole Arboleda Amoroso, Nicole Abigail Cenizal Cham, Paulo Mari Chico Cruz, Candice Ria Estacamento Monsale, Micah Gabriela Tongol San Jose, Jeremaiah Manuel Opinian