scholarly journals A Supervised Approach to Predict the Hierarchical Structure of Conversation Threads for Comments

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
A. Balali ◽  
H. Faili ◽  
M. Asadpour
Keyword(s):  
Social Media ◽  
Online News ◽  
Sources Of Information ◽  
Chronological Order ◽  
News Websites ◽  
News Agencies ◽  
Semantic Tree ◽  
The Hierarchical Structure ◽  
Thread Structure ◽  
The Web

User-generated texts such as comments in social media are rich sources of information. In general, the reply structure of comments is not publicly accessible on the web. Websites present comments as a list in chronological order. This way, some information is lost. A solution for this problem is to reconstruct the thread structure (RTS) automatically. RTS predicts a semantic tree for the reply structure, useful for understanding users’ behaviours and facilitating follow of the actual conversation streams. This paper works on RTS task in blogs, online news agencies, and news websites. These types of websites cover various types of articles reflecting the real-world events. People with different views participate in arguments by writing comments. Comments express opinions, sentiments, or ideas about articles. The reply structure of threads in these types of websites is basically different from threads in the forums, chats, and emails. To perform RTS, we define a set of textual and nontextual features. Then, we use supervised learning to combine these features. The proposed method is evaluated on five different datasets. The accuracy of the proposed method is compared with baselines. The results reveal higher accuracy for our method in comparison with baselines in all datasets.

Bots or journalists? News sharing on Twitter

2015 ◽  
Vol 40 (3) ◽  
Author(s):  
Anders Olof Larsson ◽  
Moe Hallvard
Keyword(s):  
Social Media ◽  
Online Communication ◽  
Online News ◽  
Highly Active ◽  
Media Services ◽  
Web Social ◽  
Online News Sites ◽  
News Sharing ◽  
Directing Attention ◽  
The Web

AbstractOnline news sites have become an internet ‘staple’, but we know little of the forces driving the popularity of such sites in relation to what could be understood as the latest iteration of the web – social media services. This research in brief article discusses empirical results regarding the uses of Twitter for news sharing. Specifically, we present a comparative analysis of links emanating from the service at hand to a series of media outlets over a six-month period in two countries; Sweden and Norway. Focusing on linking practices among highly active Twitter accounts, we problematize the assumption that online communication involves two or more humans by directing attention to more or less automated ‘bot’ accounts. In sum, it is suggested that such automated accounts need to be dealt with more explicitly by researchers as well as practitioners interested in the popularity of online news as expressed through social media activity.

scholarly journals Online News User Journeys: The Role of Social Media, News Websites, and Topics

2020 ◽  
Vol 8 (9) ◽  
pp. 1114-1141 ◽  
Author(s):  
Susan Vermeer ◽  
Damian Trilling ◽  
Sanne Kruikemeier ◽  
Claes de Vreese
Keyword(s):  
Social Media ◽  
Online News ◽  
News Websites

Integrated framework for criminal network extraction from Web

2019 ◽  
pp. 016555151988860
Author(s):  
Salim Afra ◽  
Reda Alhajj
Keyword(s):  
Social Media ◽  
Text Analysis ◽  
Web Application ◽  
Sources Of Information ◽  
Web Documents ◽  
Integrated Framework ◽  
Online Newspapers ◽  
Criminal Groups ◽  
Different Sources ◽  
The Web

Extracting criminals’ information and discovering their network are techniques that investigators often rely on to get extra information about criminal incidents and potential criminals. With the recent advances of the Web, a.k.a. Web 2.0, it has become a rich source of data which provides a variety of information sources. In this article, we propose an integrated framework that combines a variety of available components and makes use of different sources of information provided on the Web to get a better knowledge about criminals or terrorists (we will use criminals to cover all terrorists in the rest of this article). Our system extracts criminals’ information and their corresponding network using Web sources, such as online newspapers, official reports, and social media. It uses text analysis to identify key persons and topics from crawled Web documents. We build a criminal graph from the analysed text based on the co-occurrence of mentioning of criminals. Further analysis is applied on the constructed graph to get key people, hidden relationships and interactions between criminals, as well as hierarchical criminal groups within a network. For every process in the framework, we analysed various available works and implementations that could be used in the process. While analysing social media posts, we identified several challenges which show what solutions could be used for that purpose. Finally, we provide a Web application which implements the proposed framework. It also shows how helpful and efficient the system is in extracting and analysing criminal information.

scholarly journals Fake News Detection on Social Media

2020 ◽  
pp. 1132-1137
Author(s):  
Dipti Chaudhari ◽  
Krina Rana ◽  
Radhika Tannu ◽  
Snehal Yadav
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Smart Phone ◽  
Online News ◽  
Support Vector ◽  
Fake News ◽  
News Sources ◽  
Application Architecture ◽  
News Websites ◽  
Facebook Pages

Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication. The question is how to authenticate the news and the articles which are circulated among the social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs and social networking sites. It can be considered that social media has replaced the traditional media and become one of the main platforms for spreading news. News on social media trends to travel faster and easier than traditional news sources due to the internet accessibility and convenience. It is harmful for the society to believe on the rumors and pretend to be a news. The basic need of an hour is to stop the rumors especially in the developing countries like India, and focus on the correct, authenticated news articles. This paper demonstrates a model and methodology for fake news detection. With the help of Machine Learning, we tried to aggregate the news and later determine whether the news is real or fake using Support Vector Machine. Even we have presented the mechanism to identify the significant Tweet's attribute and application architecture to systematically automate the classification of the online news.

Mapping Covid-19 Governance in Lebanon: Territories of Sectarianism and Solidarity

2021 ◽  
pp. 1-20
Author(s):  
Mona Harb ◽  
Ahmad Gharbieh ◽  
Mona Fawaz ◽  
Luna Dayekh
Keyword(s):  
Social Media ◽  
Political Parties ◽  
News Media ◽  
Political System ◽  
Online News ◽  
Sources Of Information ◽  
Public Agencies

Abstract Many states, including Lebanon, have used the Covid-19 pandemic as an occasion to reassert their power and to consolidate their policing and repressive apparatuses. We are far from a seamless scenario, however. Rather than a mere reproduction of the sectarian political system, we argue in this paper that the governance of the pandemic in Lebanon reveals tensions between powerful political parties, weakened public agencies, as well as multiple solidarity groups with diverging aspirations, colliding over the imagined future of the country. Using various sources of information (broadcast, print and online news media, social media), we build a database of the types of actors and the categories of actions across locations, and analyze the territorial and political variations of the governance of the pandemic. The paper demonstrates that the Covid-19 response in Lebanon operates through ongoing negotiations over the national territory in which timid yet visible aspirations for a non-sectarian country confront sectarian territorialities through back-and-forth cycles.

scholarly journals Unified Representation of Twitter and Online News Using Graph and Entities

2021 ◽  
Vol 4 ◽  
Author(s):  
Munira Syed ◽  
Daheng Wang ◽  
Meng Jiang ◽  
Oliver Conway ◽  
Vishal Juneja ◽  
...  
Keyword(s):  
Social Media ◽  
Online News ◽  
Consumer Engagement ◽  
Digital Platforms ◽  
Digital News ◽  
News Agencies ◽  
Timely Fashion ◽  
Unification Problem ◽  
Different Content ◽  
News Services

To improve consumer engagement and satisfaction, online news services employ strategies for personalizing and recommending articles to their users based on their interests. In addition to news agencies’ own digital platforms, they also leverage social media to reach out to a broad user base. These engagement efforts are often disconnected with each other, but present a compelling opportunity to incorporate engagement data from social media to inform their digital news platform and vice-versa, leading to a more personalized experience for users. While this idea seems intuitive, there are several challenges due to the disparate nature of the two sources. In this paper, we propose a model to build a generalized graph of news articles and tweets that can be used for different downstream tasks such as identifying sentiment, trending topics, and misinformation, as well as sharing relevant articles on social media in a timely fashion. We evaluate our framework on a downstream task of identifying related pairs of news articles and tweets with promising results. The content unification problem addressed by our model is not unique to the domain of news, and thus can be applicable to other problems linking different content platforms.

scholarly journals Social and Non Social Media Users During The COVID-19 Pandemic Confinement Period in Canada: The "Plugged-In", Unplugged and Other Population Segments

2020 ◽  
Author(s):  
Fernando Mata ◽  
Jennifer Dumoulin
Keyword(s):  
Social Media ◽  
Market Segmentation ◽  
Online News ◽  
Sources Of Information ◽  
Information Share ◽  
Canadian Population ◽  
Segmentation Analysis ◽  
Survey Sample ◽  
Data Source ◽  
Statistics Canada

Canadians are using a variety of social and non-social media vehicles to gather information, share experiences and express anxieties during the COVID-19 confinement period. The purpose of the study is to produce a portrait of media use in Canada, paying special attention to the typical population segments in the Canadian population differentiated by their media vehicles and sources of information about the pandemic. The study used as its data source a survey sample of 4,600 adult Canadians aged 15 years old and over during the period of July 20-26 2020, and collected by Statistics Canada. Media user activities comprised a set of 11 dichotomous scales collecting data on main sources of information such as social media posts, online news, online magazines, video platforms, e-mails as well as non internet-based sources. A market segmentation analysis of these scales using Principal Components and k-means cluster analysis revealed the presence of six major population segments: Social Media Buffs (27%), News Followers (33%), Unplugged (10%),Plugged-In (9%), E-Mailers (7%) and Mixed Source Users (16%). The segment mottos were as follows: "Social Media Influencers Know Their Stuff!", "Track Those Headlines!", "I’ve Got My Own Info Sources About The Pandemic!", "Did You Read The Last Blog?" "My People Know Better!" and "Better Info Means More Choices!". This study suggests that media users in Canada constitute a very diverse group of individuals who are engaged in social and non social media to obtain timely information about the pandemic. However, they can also be exposed to inaccurate, misleading information about the virus, its transmission and its treatments. In this light, market segmentation may be a useful tool for decision makers to categorize population members by their typical attitudinal traits and, by doing so, facilitate better public campaigns directed at population segments, help design messages, and implement changes that can promote more efficient ways to deal with their target audiences.

scholarly journals Strategi Tim Visual Indozone.Id Dalam Perancangan Infografik Di Media Sosial Instagram

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Rizzy Andika Al Fathan ◽  
Amin Aminudin
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Online News ◽  
Media Ecology ◽  
Online Media ◽  
Research Subjects ◽  
News Agencies ◽  
Qualitative Descriptive ◽  
The Media ◽  
Descriptive Method

This study aims to see how the strategy of the indozone.id visual team in designing infographics on Instagram social media. The research statement proposed is how the strategy of the indozone.id visual team in designing infographics on Instagram social media? In this study using a qualitative descriptive method based on the constructivist paradigm. The research subjects were the Visual Team, Editors, and Followers of the indozone Instagram account. With the data collection techniques of observation, interviews and documentation conducted through key-information and informants, this study uses the Media Ecology theory from MC. Luhan. In its implementation, online media owners produce various elements in the news they make. Online news agencies are always prone to convey unverified information to the wider community which results in misperception and misinterpretation of news that has facts. Therefore the focus of this research is the strategy of the indozone.id visual team in designing infographics on social media Instagram. The results of this study can be seen that the strategies implemented by indozone.id include making infographics easy to understand, interesting titles, looking for news to be used as infographics, obstacles when making infographics. This strategy was carried out by the visual team in presenting the infographic. Keywords: Strategy, Online Media, Infographics, Instagram

scholarly journals An Analytical Study of the Strategies Used in Translating Trump's Tweets into Arabic

2019 ◽  
Author(s):  
Mohammed Juma Zagood
Keyword(s):  
Social Media ◽  
Analytical Study ◽  
Translation Studies ◽  
Online News ◽  
Web Pages ◽  
Donald Trump ◽  
Translation Strategies ◽  
American President ◽  
News Agencies ◽  
Media Research

It is increasingly interesting that one of the new focuses of translation studies is the translatability of the short posts on social media. Research in translating social media posts has recently received a greater attention among translation studies specialists. This paper looks firstly at Twitter as a growing social media networking and its language and, secondly, shedding some light on translation strategies used in translating English tweets into Arabic. Posts on Twitter, ‘tweets,’ by well-known figures are followed, translated, and reposted in other languages every day. Strategies used by Arab translators vary depending on the importance of the tweet as well as the ideology of the translator and the institutions they work for. This paper, therefore, investigates the translation strategies adopted by the Arab online news agencies, mentioned later, on their web pages in translating some tweets posted by the American President, Donald Trump in his first month of presidency. The analysis draws on Vinay and Darbelnet’s (1958/1995) model and Nida’s (1964) translation strategies.

scholarly journals Who Shares and Comments on News?: A Cross-National Comparative Analysis of Online and Social Media Participation

2017 ◽  
Vol 3 (4) ◽  
pp. 205630511773575 ◽  
Author(s):  
Antonis Kalogeropoulos ◽  
Samuel Negredo ◽  
Ike Picone ◽  
Rasmus Kleis Nielsen
Keyword(s):  
Social Media ◽  
Comparative Analysis ◽  
Digital Media ◽  
Online News ◽  
Media Technologies ◽  
News Stories ◽  
High Interest ◽  
News Websites ◽  
Social Media Platforms ◽  
Cross National

In this article, we present a cross-national comparative analysis of which online news users in practice engage with the participatory potential for sharing and commenting on news afforded by interactive features in news websites and social media technologies across a strategic sample of six different countries. Based on data from the 2016 Reuters Institute Digital News Report, and controlling for a range of factors, we find that (1) people who use social media for news and a high number of different social media platforms are more likely to also engage more actively with news outside social media by commenting on news sites and sharing news via email, (2) political partisans on both sides are more likely to engage in sharing and commenting particularly on news stories in social media, and (3) people with high interest in hard news are more likely to comment on news on both news sites and social media and share stores via social media (and people with high interest in any kind of news [hard or soft] are more likely to share stories via email). Our analysis suggests that the online environment reinforces some long-standing inequalities in participation while countering other long-standing inequalities. The findings indicate a self-reinforcing positive spiral where the already motivated are more likely in practice to engage with the potential for participation offered by digital media, and a negative spiral where those who are less engaged participate less.

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