Finding Influential Users in Social Media Using Association Rule Learning

Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user participation. Normally, the success of a social media site is dependent on the activity level of the participating users. For both online social networking sites and individual users, it is of interest to find out if a topic will be interesting or not. In this article, we propose association learning to detect relationships between users. In order to verify the findings, several experiments were executed based on social network analysis, in which the most influential users identified from association rule learning were compared to the results from Degree Centrality and Page Rank Centrality. The results clearly indicate that it is possible to identify the most influential users using association rule learning. In addition, the results also indicate a lower execution time compared to state-of-the-art methods

Seed selection for information cascade in multilayer networks

Information spreading is an interesting field in the domain of online social media. In this work, we are investigating how well different seed selection strategies affect the spreading processes simulated using independent cascade model on eighteen multilayer social networks. Fifteen networks are built based on the user interaction data extracted from Facebook public pages and tree of them are multilayer networks downloaded from public repository (two of them being Twitter networks). The results indicate that various state of the art seed selection strategies for single-layer networks like K-Shell or VoteRank do not perform so well on multilayer networks and are outperformed by Degree Centrality

Linguistic Markers of Influence in Informal Interactions

There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily interactions. Motivated by the basic principles of influence, we attempt to identify indicative linguistic features of the posts in an online knitting community. We present the scheme used to operationalize and label the posts with indicator features. Experiments with the identified features show an improvement in the classification accuracy of influence by 3.15%. Our results illustrate the important correlation between the characteristics of the language and its potential to influence others.Comment: 10 pages, Accepted in NLP+CSS workshop for ACL (Association for Computational Linguistics) 201

Fair Use Challenges in Academic and Research Libraries

Summarizes findings from a survey of librarians on the application of fair use in copyright practice to fulfill libraries' missions of teaching and learning support, scholarship support preservation, exhibition, and public outreach

The applications of social media in sports marketing

n the era of big data, sports consumer's activities in social media become valuable assets to sports marketers. In this paper, the authors review extant literature regarding how to effectively use social media to promote sports as well as how to effectively analyze social media data to support business decisions. Methods: The literature review method. Results: Our findings suggest that sports marketers can use social media to achieve the following goals, such as facilitating marketing communication campaigns, adding values to sports products and services, creating a two-way communication between sports brands and consumers, supporting sports sponsorship program, and forging brand communities. As to how to effectively analyze social media data to support business decisions, extent literature suggests that sports marketers to undertake traffic and engagement analysis on their social media sites as well as to conduct sentiment analysis to probe customer's opinions. These insights can support various aspects of business decisions, such as marketing communication management, consumer's voice probing, and sales predictions. Conclusion: Social media are ubiquitous in the sports marketing and consumption practices. In the era of big data, these ＂footprints＂ can now be effectively analyzed to generate insights to support business decisions. Recommendations to both the sports marketing practices and research are also addressed

The non-use and influence of UK energy sector indicators

This paper presents the results from a case study on the role in policymaking of UK Energy Sector Indicators (ESIs), introduced by the government in 2003. The findings show that the ESIs constituted a very minor element within the broader evidence-base used by policymakers, and that this indicator set and its objectives were poorly known even to central players in the sector. The findings of this research provide further evidence for the observation that scientific knowledge (including evaluations, assessments and indicators) seldom play an instrumental role in policymaking, and are more likely to produce indirect, conceptual and political impacts. The analysis provides a number of tentative conclusions concerning such potential indirect impacts that accrue mainly through processes of dialogue and argumentation both during the preparation of the indicators and after their publication as part of the annual reporting by the UK energy department. The ESIs have played various conceptual and political roles, yet the concrete outcomes in terms of policy change remain to be explored. The conclusions highlight the limitations of rationalist notions of direct, instrumental use in the efforts to understand the role of indicators in policymaking. The paper concludes by three tentative propositions concerning the explanations to the absence of instrumental role of the ESIs, which could be usefully explored in future research: the characteristics of the energy sector; the characteristics of the UK policy culture; and the exceptionality of the ESIs in the general evidence-base of UK energy sector

Mapping the Money in Public Media

Provides an overview of emerging "user-centric" business models for public media that utilize the interactivity of digital technologies as a way to integrate content, communication, commerce, and community through participatory media creation