Digital Digging: Using Social Media to Shed Light on Investigations
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Significant of Social Media and Event Marketing in Developing Countries
The Ministry of Education of Azerbaijan Republic Significant of Social Media and Event Marketing in Developing Countries Amina Azadli UNEC SABAH Azerbaijan State Economic University MAY 2018 ACKNOWLEDGEMENT First of all, I am very grateful to everyone who supported me for my dissertation. I would like to express my thanks to my advisor Sabina Akberova. My special thanks go to Elshan Mehtiyev and my family. They gave me moral support during preparation of dissertation. 2 ABSTRACT Under changing world conditions, people see that things change rapidly, either technologically or humanly. People are better able to understand the extent to which this change is compared to changes. In today's consumer- dominated world, marketing executives must evaluate every opportunity they face to start a relationship with the buyer. Marketers must focus on winning a good name and image on the market and earn the trust of their customers. To do this, it must be tightly packed with marketing tools and tactics that require the least amount of time and money. But in reality, achieving this business is not about companies. A sound marketing mix involving Social Media Marketing is crucial for connecting as many potential customers as possible. In this study, social media and event marketing were discussed in developing countries where the young population is older than the elderly and social media is used more by young people. On the topics of Social Media and Event Marketing, a literature study was performed first. Later, a research study was conducted among the citizens of the Developing Country in Social Media and Event marketing. -
The Versatility of Microblogging
www.spireresearch.com Side Click: The versatility of microblogging Microblogging is well-established globally as a way of keeping in touch with others about events occurring in their lives in real-time. Popular microblogging sites include Twitter in the U.S., Tencent QQ in China and Me2day in South Korea. Twitter has 140 million active users1, while China’s Tencent QQ has a staggering 721 million active user accounts2, ranking only behind Facebook in terms of being the most used social networking service worldwide. Microblogging allows users to combine blogging and instant messaging to post short messages on their profiles3; including small and conversational talk, self-promotion, spam and news 4 . On a deeper level, microblogging has altered the way people consume and generate information – not only democratizing the broadcasting of information but also enabling it to be done in real-time. Connecting to stakeholders There are several benefits to integrating microblogging into a business’s regular stakeholder communication regime. Consumers who “follow” a company’s products or services would be the first to know of any promotions. The company also benefits through obtaining prompt feedback and suggestions for improvement. A concerned investor 1 Twitter turns six, Twitter Blog, 21 March 21 2012 2 QQ Continues to Dominate Instant Messaging in China, eMarketer Inc., 27 April 2012 3 An Insight Into Microblogging Trends And Toolbars, ArticlesXpert,21 January 2012 4 Twitter Study – August 2009, PearAnalytics.com, August 2009 © 2012 Spire Research and Consulting Pte Ltd would want to be the first to know of any important news which might impact her returns. -
SOCIAL MEDIA MINING Introduction Dear Instructors/Users of These Slides
SOCIAL MEDIA MINING Introduction Dear instructors/users of these slides: Please feel free to include these slides in your own material, or modify them as you see fit. If you decide to incorporate these slides into your presentations, please include the following note: R. Zafarani, M. A. Abbasi, and H. Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014. Free book and slides at http://socialmediamining.info/ or include a link to the website: http://socialmediamining.info/ Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 22 Facebook • How does Facebook use your data? Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 33 What about Amazon? Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 44 Or Twitter? Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 55 Objectives of Our Course • Understand social aspects of the Web – Social Theories + Social media + Mining – Learn to collect, clean, and represent social media data – How to measure important properties of social media and simulate social media models – Find and analyze communities in social media – Understand how information propagates in social media – Understanding friendships in social media, perform recommendations, and analyze behavior • Study or ask interesting research issues – e.g., start-up ideas / research challenges • Learn representative algorithms and tools Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 66 Social Media Social Media Mining http://socialmediamining.info/ MeasuresIntroduction and Metrics 77 Definition Social Media is the use of electronic and Internet tools for the purpose of sharing and discussing information and experiences with other human beings in more efficient ways. -
The Limits of Commercialized Censorship in China
The Limits of Commercialized Censorship in China Blake Miller∗ September 27, 2018 Abstract Despite massive investment in China's censorship program, internet platforms in China are rife with criticisms of the government and content that seeks to organize opposition to the ruling Communist Party. Past works have attributed this \open- ness" to deliberate government strategy or lack of capacity. Most, however, do not consider the role of private social media companies, to whom the state delegates information controls. I suggest that the apparent incompleteness of censorship is largely a result of principal-agent problems that arise due to misaligned incentives of government principals and private media company agents. Using a custom dataset of annotated leaked documents from a social media company, Sina Weibo, I find that 16% of directives from the government are disobeyed by Sina Weibo and that disobedience is driven by Sina's concerns about censoring more strictly than com- petitor Tencent. I also find that the fragmentation inherent in the Chinese political system exacerbates this principal agent problem. I demonstrate this by retrieving actual censored content from large databases of hundreds of millions of Sina Weibo posts and measuring the performance of Sina Weibo's censorship employees across a range of events. This paper contributes to our understanding of media control in China by uncovering how market competition can lead media companies to push back against state directives and increase space for counterhegemonic discourse. ∗Postdoctoral Fellow, Program in Quantitative Social Science, Dartmouth College, Silsby Hall, Hanover, NH 03755 (E-mail: [email protected]). 1 Introduction Why do scathing criticisms, allegations of government corruption, and content about collective action make it past the censors in China? Past works have theorized that regime strategies or state-society conflicts are the reason for incomplete censorship. -
A Conceptual Framework for the Mining and Analysis of the Social Media Data 1
International Journal of Database Theory and Application Vol. 10, No.10 (2017), pp. 11-34 hhtp://dx.doi.org/10.14257/ijdta.2017.10.10.02 A Conceptual Framework for the Mining and Analysis of the Social Media Data 1 Sethunya R Joseph1*, Keletso Letsholo2 and Hlomani Hlomani3 1,2,3 Computer Science Department, Botswana International University of Science and Technology, Palapye, Botswana [email protected], [email protected] [email protected] Abstract Social media data possess the characteristics of Big Data such as volume, veracity, velocity, variability and value. These characteristics make its analysis a bit more challenging than conventional data. Manual analysis approaches are unable to cope with the fast pace at which data is being generated. Processing data manually is also time consuming and requires a lot of effort as compared to using computational methods. However, computational analysis methods usually cannot capture in-depth meanings (semantics) within data. On their individual capacity, each approach is insufficient. As a solution, we propose a Conceptual Framework, which integrates both the traditional approaches and computational approaches to the mining and analysis of social media data. This allows us to leverage the strengths of traditional content analysis, with its regular meticulousness and relative understanding, whilst exploiting the extensive capacity of Big Data analytics and accuracy of computational methods. The proposed Conceptual Framework was evaluated in two stages using an example case of the political landscape of Botswana data collected from Facebook and Twitter platforms. Firstly, a user study was carried through the Inductive Content Analysis (ICA) process using the collected data. -
A Social Media Mining and Ensemble Learning Model: Application to Luxury and Fast Fashion Brands
information Article A Social Media Mining and Ensemble Learning Model: Application to Luxury and Fast Fashion Brands Yulin Chen Department of Mass Communication, Tamkang University, New Taipei City 25137, Taiwan; [email protected] Abstract: This research proposes a framework for the fashion brand community to explore public participation behaviors triggered by brand information and to understand the importance of key image cues and brand positioning. In addition, it reviews different participation responses (likes, comments, and shares) to build systematic image and theme modules that detail planning require- ments for community information. The sample includes luxury fashion brands (Chanel, Hermès, and Louis Vuitton) and fast fashion brands (Adidas, Nike, and Zara). Using a web crawler, a total of 21,670 posts made from 2011 to 2019 are obtained. A fashion brand image model is constructed to determine key image cues in posts by each brand. Drawing on the findings of the ensemble analysis, this research divides cues used by the six major fashion brands into two modules, image cue module and image and theme cue module, to understand participation responses in the form of likes, comments, and shares. The results of the systematic image and theme module serve as a critical reference for admins exploring the characteristics of public participation for each brand and the main factors motivating public participation. Keywords: fashion brands; luxury brands; masstige; key image cues; social media mining; ensem- ble earning Citation: Chen, Y. A Social Media Mining and Ensemble Learning Model: Application to Luxury and Fast Fashion Brands. Information 2021, 1. Introduction 12, 149. -
Data Mining Techniques for Social Media Analysis
Advances in Engineering Research (AER), volume 142 International Conference for Phoenixes on Emerging Current Trends in Engineering and Management (PECTEAM 2018) A Survey: Data Mining Techniques for Social Media Analysis 1Elangovan D, 2Dr.Subedha V, 3Sathishkumar R, 4 Ambeth kumar V D 1Research scholar, Department of Computer Science Engineering, Sathyabama University, India 2Professor, Department of Computer Science Engineering, Panimalar Institute of Technology, Chennai, India 3Assistant Professor, 4Associate Professor, Department of Computer Science Engineering, Panimalar Engineering College, Chennai, India [email protected],[email protected], [email protected],[email protected] Abstract—Data mining is the extraction of present information databases. The overall objective of the data mining technique from high volume of data sets, it’s a modern technology. The is to extract information from a huge data set and transform it main intention of the mining is to extract the information from a into a comprehensible structure for more use. The different large no of data set and convert it into a reasonable structure for data Mining techniques are further use. The social media websites like Facebook, twitter, instagram enclosed the billions of unrefined raw data. The I. Characterization. various techniques in data mining process after analyzing the II. Classification. raw data, new information can be obtained. Since this data is III. Regression. active and unstructured, conventional data mining techniques IV. Association. may not be suitable. This survey paper mainly focuses on various V. Clustering. data mining techniques used and challenges that arise while using VI. Change Detection. it. The survey of various work done in the field of social network analysis mainly focuses on future trends in research. -
NIST Data Science Symposium Proceedings
March 4-5 Data Science Symposium Proceedings 2014 Abstracts for posters presented at the 2014 NIST Data Science Symposium on March 4th 2014 Version 1.1 TABLE OF CONTENTS A CONCEPTUAL FRAMEWORK FOR HEALTH DATA HARMONIZATION .................................................................... 6 LEWIS E. BERMAN, & YAIR G. RAJWAN, ............................................................................................................................. 6 ICF International & Visual Science Informatics ...................................................................................................... 6 REAL-TIME ANALYTICS FOR DATA SCIENCE ............................................................................................................ 7 HIROTAKA OGAWA ......................................................................................................................................................... 7 National Institute of Advance Industrial Science and Technology, JAPAN ............................................................. 7 UTILIZATION OF A VISUAL ANALYTICAL APPROACH TO DETECT ANOMALIES IN LARGE NETWORK TRAFFIC DATA . 7 LASSINE CHERIF, SOO-YEON JI, DONG HYUN JEONG .............................................................................................................. 7 Department of Computer Science and Information Technology, Univ. of the District of Columbia and Dept. of Computer Science, Bowie State University ........................................................................................................... -
Statistical Data Mining for Sina Weibo, a Chinese Micro-Blog: Sentiment Modelling and Randomness Reduction for Topic Modelling
Statistical Data Mining for Sina Weibo, a Chinese Micro-blog: Sentiment Modelling and Randomness Reduction for Topic Modelling London School of Economics and Political Sciences Wenqian Cheng A thesis submitted to the Department of Statistics of the London School of Economics for the degree of Doctor of Philosophy, London, March 2017 2 Declaration I certify that the thesis I have presented for examination for the MPhil/PhD degree of the London School of Economics and Political Science is solely my own work other than where I have clearly indicated that it is the work of others (in which case the extent of any work carried out jointly by me and any other person is clearly identified in it). The copyright of this thesis rests with the author. Quotation from it is permitted, provided that full acknowledgement is made. This thesis may not be reproduced without my prior written consent. I warrant that this authorisation does not, to the best of my belief, infringe the rights of any third party. I declare that my thesis consists of approximately 50,000 words. 1 Abstract Before the arrival of modern information and communication technology, it was not easy to capture people's thoughts and sentiments; however, the development of statistical data mining techniques and the prevalence of mass social media provide opportunities to capture those trends. Among all types of social media, micro-blogs make use of the word limit of 140 characters to force users to get straight to the point, thus making the posts brief but content-rich resources for investigation. -
A Machine Learning Based Classification for Social Media Messages
ISSN (Print) : 0974-6846 Indian Journal of Science and Technology, Vol 8(16), DOI: 10.17485/ijst/2015/v8i16/63640, July 2015 ISSN (Online) : 0974-5645 A Machine Learning based Classification for Social Media Messages R. Nivedha* and N. Sairam School of Computing, SASTRA University, Thanjavur – 613 401, Tamil Nadu, India; [email protected] Abstract A social media is a mediator for communication among people. It allows user to exchange information in a useful way. Twitter is one of the most popular social networking services, where the user can post and read the tweet messages. The Twitter data cannot classify directly since it has noisy information. This noisy information is removed by preprocessing. The tweet messages are helpful for biomedical, research and health care fields. The data are extracted from the Twitter. The using precision, error rate and accuracy. The result is compared with the Naïve Bayesian and the proposed method yields hpilagihn p terxfto irsm claanscseif ireeds uinltt oth haena ltthhe a Nnadï vneo nB-ahyeeaslitahn d. Iatt ap eursfionrgm CsA wRTel al lwgoitrhi tthhme .l aTrhgee p deartfao rsmeta anncde oitf icsl assimsifpilcea tainodn iesf faencatilvyez.e Idt yKielydsw hoigrhd csl:assification accuracy and the resulting data could be used for further mining. CART, Classification, Decision Tree, Machine Learning, Twitter 1. Introduction provides an accurate prediction and also improves the performance of the results. The social media has now become a center of information exchange. It includes an online communication channel 2. Previous work for community-based input, interaction, content sharing and collaboration among people. Social media technolo- The literature surveys on text classification which is gies are in different forms such as internet forum, blogs, related to our work are discussed below. -
Tencent and China Mobile's Dilemma
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by AIS Electronic Library (AISeL) Association for Information Systems AIS Electronic Library (AISeL) Pacific Asia Conference on Information Systems PACIS 2014 Proceedings (PACIS) 2014 FROM WECHAT TO WE FIGHT: TENCENT AND CHINA MOBILE’S DILEMMA Jun Wu School of Economics and Management, Beijing University of Posts and Telecommunications, [email protected] Qingqing Wan School of Economics and Management, Beijing University of Posts and Telecommunications, [email protected] Follow this and additional works at: http://aisel.aisnet.org/pacis2014 Recommended Citation Wu, Jun and Wan, Qingqing, "FROM WECHAT TO WE FIGHT: TENCENT AND CHINA MOBILE’S DILEMMA" (2014). PACIS 2014 Proceedings. 265. http://aisel.aisnet.org/pacis2014/265 This material is brought to you by the Pacific Asia Conference on Information Systems (PACIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in PACIS 2014 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. FROM WECHAT TO WE FIGHT: TENCENT AND CHINA MOBILE’S DILEMMA Jun Wu, School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China, [email protected] Qingqing Wan, School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China, [email protected] Abstract With the coming of mobile internet era, Giants in the different industry begin to compete face by face. This teaching case presents the event of charging for WeChat in China context to delineate the new challenges that Online Service Provider and Mobile Network Operator will face. -
Weibo's Role in Shaping Public Opinion and Political
Blekinge Institute of Technology School of Computing Department of Technology and Aesthetics WEIBO’S ROLE IN SHAPING PUBLIC OPINION AND POLITICAL PARTICIPATION IN CHINA Shajin Chen 2014 BACHELOR THESIS B.S. in Digital Culture Supervisor: Maria Engberg Chen 1 Table of Contents 1. INTRODUCTION .............................................................................................................2 2. INTERNET AND MICROBLOGGING IN CHINA ......................................................5 2.1 INTERNET, MEDIA AND POLITICAL LANDSCAPE IN CHINA: AN OVERVIEW .......................... 5 2.2 MICROBLOGGING AND CHINESE WEIBO .........................................................................7 2.3 SINA WEIBO: THE KING OF MICROBLOGGING IN CHINA ................................................... 8 3. DOMINANT FEATURES OF WEIBO IN SHAPING PUBLIC OPINION AND POLITICAL SPHERE ........................................................................................................10 3.1 INFORMATION DIFFUSION ............................................................................................11 3.2 OPINION LEADERS AND VERIFIED IDENTITY ..................................................................12 3.3 PLATFORM FOR FREE SPEECH, COLLECTIVE VOICE AND EXPOSURE ................................. 14 3.4 PARTICIPATION OF MASS MEDIA AND GOVERNMENT ......................................................15 4. CASE STUDIES ..............................................................................................................18 4.1