Understanding Citizen Reactions and Ebola-Related Information Propagation on Social Media

In severe outbreaks such as Ebola, bird flu and SARS, people share news, and their thoughts and responses regarding the outbreaks on social media. Understanding how people perceive the severe outbreaks, what their responses are, and what factors affect these responses become important. In this paper, we conduct a comprehensive study of understanding and mining the spread of Ebola-related information on social media. In particular, we (i) conduct a large-scale data-driven analysis of geotagged social media messages to understand citizen reactions regarding Ebola; (ii) build information propagation models which measure locality of information; and (iii) analyze spatial, temporal and social properties of Ebola-related information. Our work provides new insights into Ebola outbreak by understanding citizen reactions and topic-based information propagation, as well as providing a foundation for analysis and response of future public health crises.Comment: 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016

Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media

With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression from tweets obtained unobtrusively. Based on the analysis of tweets crawled from users with self-reported depressive symptoms in their Twitter profiles, we demonstrate the potential for detecting clinical depression symptoms which emulate the PHQ-9 questionnaire clinicians use today. Our study uses a semi-supervised statistical model to evaluate how the duration of these symptoms and their expression on Twitter (in terms of word usage patterns and topical preferences) align with the medical findings reported via the PHQ-9. Our proactive and automatic screening tool is able to identify clinical depressive symptoms with an accuracy of 68% and precision of 72%.Comment: 8 pages, Advances in Social Networks Analysis and Mining (ASONAM), 2017 IEEE/ACM International Conferenc

Capturing Emerging Realities in Citizen Engagement in Science in Social Media : A Social Media Analytics Protocol for the Allinteract Study

In the digital era, social media has become a space for the socialization and interaction of citizens, who are using social networks to express themselves and to discuss scientific advances with citizens from all over the world. Researchers are aware of this reality and are increasingly using social media as a source of data to explore citizens' voices. In this context, the methods followed by researchers are mainly based on the content analysis using manual, automated or combined tools. The aim of this article is to share a protocol for Social Media Analytics that includes a Communicative Content Analysis (CCA). This protocol has been designed for the Horizon 2020 project Allinteract, and it includes the social impact in social media methodology. The novel contribution of this protocol is the detailed elaboration of methods and procedures to capture emerging realities in citizen engagement in science in social media using a Communicative Content Analysis (CCA) based on the contributions of Communicative Methodology (CM).Peer reviewe

Transformasi Fungsi Komunikator Dan Fungsi Konstruksi Akun Facebook Presiden SBY

: New media in a form of social media has grown rapidly nowadays. The growth of social media is supported by technological advances connected people around the world. They are connected to each other and easily exchange messages. The transformation has finally weakened the media itself. This is a concept paper combining two methodoloies, namely literature review and content analysis of Presiden Yudhoyono’s Facebook account. This paper reveals that public connectedness within digital era has brought back the media to its original function; media that has only message distribution function, without having message construction function.

The Impact of YouTube and Family on Religiusity Behavior and Pro-Social Behavior of Teenagers in The City of Sidoarjo: Dampak Media Sosial YouTube dan Keluarga Terhadap Perilaku Religiusitas dan Perilaku Pro-Sosial pada Remaja di Kota Sidoarjo

YouTube social media is one part of changes in technological advances that provide information openly to its users, so that it can indirectly have an impact, especially among teenagers. Given how YouTube's social media is very easy to access by various groups, this research aims to analysis the impact that the use of YouTube and family social media has on religious behavior and pro-social behavior of teenagers, especially in the city of Sidoarjo. This type of research is quantitative with 140 young respondents in Sidoarjo City, which was taken by random sampling technique.  The data obtained in this study were obtained from filling out and distributing questionnaires. The research was completed using multiple regression analysis with the SPSS Statistics application.&nbsp

Marketing Strategy of Madilog Coffee Shop using Influencers through Instagram Social Media

Marketing Strategy of Madilog Coffee Shop using Influencers through Instagram Social Media (Case Study at Madilog Coffee Shop). This type of research uses a qualitative research design. The number of informants in this study amounted to 4 people (1 Owner and 3 Visitors). Samples will be obtained by using a purposive sampling technique. Data collection techniques can be done by way of interviews (interviews), and observations (observations), and a combination of the three, directly from respondents selected as a sample, which includes data on the identity of respondents. Based on the results obtained using qualitative analysis, it can be concluded in this study that the reason why the marketing strategy of Madilog Coffee Shop Marketing Using Influencers Through Instagram Social Media switches from conventional ways to Instagram marketing, namely, first because of technological advances using mobile phones, consumers are more often using Instagram social media, secondly by using social media marketing especially Instagram can further reduce marketing costs, Thirdly by utilizing influencers to increase marketing on Instagram, and have a positive impact on the progress of Madilog Coffee Shop using Influencers through Instagram Social Media, finally the role of place variables / place in the marketing mix can make Madilog Coffee Shop Marketing Strategies use Influencers through Instagram Social Media to come back to Madilog Coffee Shop Marketing Strategies using This Influencer Through Social Media Instagram gives and places an attractive place for consumers and the price is also in accordance with the prices of students. The place according to the researchers is less strategic but with advances in technology and promotion strategies that Madilog Coffee Shop

Stop Clickbait: Detecting and Preventing Clickbaits in Online News Media

Most of the online news media outlets rely heavily on the revenues generated from the clicks made by their readers, and due to the presence of numerous such outlets, they need to compete with each other for reader attention. To attract the readers to click on an article and subsequently visit the media site, the outlets often come up with catchy headlines accompanying the article links, which lure the readers to click on the link. Such headlines are known as Clickbaits. While these baits may trick the readers into clicking, in the long run, clickbaits usually don't live up to the expectation of the readers, and leave them disappointed. In this work, we attempt to automatically detect clickbaits and then build a browser extension which warns the readers of different media sites about the possibility of being baited by such headlines. The extension also offers each reader an option to block clickbaits she doesn't want to see. Then, using such reader choices, the extension automatically blocks similar clickbaits during her future visits. We run extensive offline and online experiments across multiple media sites and find that the proposed clickbait detection and the personalized blocking approaches perform very well achieving 93% accuracy in detecting and 89% accuracy in blocking clickbaits.Comment: 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM