Bridging the Gap Between the Least and the Most Influential Twitter Users

Social networks play an increasingly important role in shaping the behaviour of users of the Web. Conceivably Twitter stands out from the others, not only for the platform's simplicity but also for the great influence that the messages sent over the network can have. The impact of such messages determines the influence of a Twitter user and is what tools such as Klout, PeerIndex or TwitterGrader aim to calculate. Reducing all the factors that make a person influential into a single number is not an easy task, and the effort involved could become useless if the Twitter users do not know how to improve it. In this paper we identify what specific actions should be carried out for a Twitterer to increase their influence in each of above-mentioned tools applying, for this purpose, data mining techniques based on classification and regression algorithms to the information collected from a set of Twitter users.This work has been partially founded by the European Commission Project ”SiSOB: An Observatorium for Science in Society based in Social Models” (http://sisob.lcc.uma.es) (Contract no.: FP7 266588), ”Sistemas Inalámbricos de Gestión de Información Crítica” (with code number TIN2011-23795 and granted by the MEC, Spain) and ”3DTUTOR: Sistema Interoperable de Asistencia y Tutoría Virtual e Inteligente 3D” (with code number IPT-2011-0889- 900000 and granted by the MINECO, Spain

Accounting, accountability, social media and big data: Revolution or hype?

Purpose: The purpose of this paper is to outline an agenda for researching the relationship between technology-enabled networks â such as social media and big data â and the accounting function. In doing so, it links the contents of an unfolding area research with the papers published in this special issue of Accounting, Auditing and Accountability Journal. Design/methodology/approach: The paper surveys the existing literature, which is still in its infancy, and proposes ways in which to frame early and future research. The intention is not to offer a comprehensive review, but to stimulate and conversation. Findings: The authors review several existing studies exploring technology-enabled networks and highlight some of the key aspects featuring social media and big data, before offering a classification of existing research efforts, as well as opportunities for future research. Three areas of investigation are identified: new performance indicators based on social media and big data; governance of social media and big data information resources; and, finally, social media and big dataâs alteration of information and decision-making processes. Originality/value: The authors are currently experiencing a technological revolution that will fundamentally change the way in which organisations, as well as individuals, operate. It is claimed that many knowledge-based jobs are being automated, as well as others transformed with, for example, data scientists ready to replace even the most qualified accountants. But, of course, similar claims have been made before and therefore, as academics, the authors are called upon to explore the impact of these technology-enabled networks further. This paper contributes by starting a debate and speculating on the possible research agendas ahead

Korean-popular Facebook fan page analytics in Thailand

The purpose of this study was to gather, analyze, and elaborate big data on Facebook’s essential information, with a specific focus on the information obtained from Korean-popular (K-Pop) fan pages on the social networking site. For this analysis, a total of 3,531,736 comments by Korean-pop fans were gathered from various K-pop Facebook pages. In order to interpret how 11 extremely popular Facebook pages shape Thai fans’ enthusiasm for the South Korean music industry, descriptive statistics and visualization analysis were employed. Finally, data analytics and correlation analysis were used to evaluate the essential understanding of the Facebook pages. The research revealed three key findings: i) K-pop fan pages provide more opportunities for Thai fans to express their support for K-pop artists and advocate for causes, ii) K-pop fan pages provide more opportunities for Thai fans to communicate with K-pop artists, and iii) K-pop fan pages build opportunities for Thai fans to establish a more glamorous online presence despite limitations concerning financial resources, foreign language skills, and opportunities. In the future, the research outcomes may be valuable for academic studies and practice

Social media and performance measurement systems: towards a new model?

Purpose – The purpose of this paper is to analyse how social media (SM) influence performance measurement systems (PMS), examining changes in measurement methods, performance indicators and their application. Design/methodology/approach – The framework of the research was constructed to cover the technical component of PMS (measurement methods and indicators) and the use of the information obtained from SM. Empirically, the study is based on a set of case studies in eight companies. Findings – The study findings offer a theoretical and empirical framework to evaluate PMS in the era of SM. It provides a classification of SM metrics, key performance indicators correlated to their use within different departments belonging to eight companies, highlighting the benefits and threats of SM information for PMS. Research limitations/implications – The limitation of this study is the diversity of industries included into the multiple-case study. The authors choose cases with the aim of providing a broader view on the impact of SM on PMS. However, the results show the dependency of use and type of measurement on certain industries, requiring future research focused on specific sectors or PMS aspects. Practical implications – The paper provides a map of SM information measurement methods and use, which allows companies to position themselves and examine PMS evolution. Originality/value – The results of the paper propose a holistic model, employing SM as a new variable in PMS. </jats:sec

Customer Service on Social Media: The Effect of Customer Popularity and Sentiment on Airline Response

Many companies are now providing customer service through social media, helping and engaging their customers on a real-time basis. To study this increasingly popular practice, we examine how major airlines respond to customer comments on Twitter by exploiting a large data set containing Twitter exchanges between customers and three major airlines in North America. We find that these airlines pay significantly more attention to Twitter users with more followers, suggesting that companies literarily discriminate customers based on their social influence. Moreover, our findings suggest that companies in the digital age are increasingly more sensitive to the need to answer both customer complaints and customer compliments while the actual time-to-response depends on customer’s social influence and sentiment as well as the firm’s social media strategy

Local and Global Influence on Twitter

The analysis of influence in social network is drawing more and more attention. It can be applied in different areas such as political campaigns and marketing. In this work, the analysis of influence in Twitter, based on users‟ profile statistics in a real-time scale, was studied and discussed. Two methods of identifying influential users by given keyword in real-time are introduced. To understand the relationship between users‟ influence features and social states in real life, two influence measures were presented: Local Influence which the user has on his/her immediate set of contacts and global Influence which the user has on the entire social network. This study describes in details these two metrics and shows their implementation for a real social network. Our case study, using Twitter, showed that the proposed model can create clusters of users in 2D space corresponding to their social standing, and can further be used to classify previously-unseen users into the correct classes with an f-measure of 0.82 which is significantly higher than benchmark algorithms. F-measure is often used for measuring the accuracy of the test for classification

Leveraging the social network: How journalists and news organizations connect with readers on Twitter

As journalists and newspapers have attempted to adapt to a new media environment uncertainty remains about how best to approach the use of social media while retaining the journalistic values that have served as a check against misinformation. This study examines how news producers communicate on social media and what interpersonal communication concepts are at work in a mediated social network. Using the concepts found in social network theory, the study tests the roles of interaction, self-disclosure, new journalism values, and the role of opinion leaders on Twitter. Data from the Twitter accounts of 10 newspapers and 40 journalists based in Oklahoma was collected and analyzed. The results of this analysis showed strong effects by opinion leaders and self-disclosure in message propagation. Results also showed a lack of transparency by journalists and newspapers and differences between how often they provided self-disclosure to and engaged with their audiences. However, the results also show that journalists and newspapers both missed several opportunities to better engage audiences and bring them into the conversation. Keywords: Journalism, Twitter, Social Networks, News, Medi