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An Integrated Approach of Sensing Tobacco-Oriented Activities In IEEE SYSTEMS JOURNAL, VOL. 10, NO. 3, SEPTEMBER 2016 1193 An Integrated Approach of Sensing Tobacco-Oriented Activities in Online Participatory Media Yunji Liang, Xingshe Zhou, Daniel Dajun Zeng, Senior Member, IEEE, Bin Guo, Member, IEEE, Xiaolong Zheng, Member, IEEE, and Zhiwen Yu, Senior Member, IEEE Abstract—With the embracing of mobile Internet of Things, I. INTRODUCTION participatory media is becoming a new battlefield for tobacco wars. However, how to automatically collect and analyze the ITH the development of Internet of Things (IoT), vari- large-scale user-generated data that are relevant to tobacco in W ous objects are being connected and a huge amount of participatory media is still unexplored. In this paper, we pro- data are generated each day, including the sensing data from pose an integrated approach of sensing collective activities in embedded sensors and the user-generated data in online partic- tobacco-related participatory media. Meanwhile, we compare the temporal patterns, topological patterns, and collective emotion ipatory media such as social networking sites and discussion patterns among protobacco, antitobacco, and quit-tobacco groups. forums. All these human-centered or human-contributed data Based on the proposed framework, a prototype was implemented can reflect the digital footprints/activities of citizens and are to collect large-scale tobacco-related data sets from Facebook. opening a new paradigm of intelligent IoT. Various studies have This demonstrates that the proposed framework is feasible and been done on extracting urban and social intelligence from the reasonable. Our preliminary findings reveal that, first, tobacco- related content grows exponentially. In particular, the growth of collected data from participatory media, such as social relation- the protobacco group follows the exponential law, whereas there ship mining, social recommendation, location recommendation, is linear growth for the tobacco control group. Second, the con- etc. In this paper, we address a different problem over intelligent nection between the tobacco control community and the tobacco IoT. We aim to automatically collect and analyze large-scale cessation community is tight, whereas the nodes in the protobacco tobacco-related data sets with the help of the unprecedented community are connected sparsely. Finally, the collective emotion in tobacco communities is negative. sensing capability of intelligent IoT. Many studies demonstrate that tobacco-related content on Index Terms—Facebook, Internet of Things (IoT), participatory participatory media is accumulating. For the protobacco com- media, public health, tobacco control, tobacco surveillance. munity, tobacco companies stand to greatly benefit from the marketing potential of social media without being at a signif- icant risk of being implicated in violating any laws [1], such as cigarette promotion on Facebook [2], protobacco video clips on YouTube [1], and mobile applications (“ishisha” and “Cigar Boss”) for tobacco promotion. In response to the “provoca- Manuscript received September 22, 2013; revised December 30, 2013; tion” from the protobacco community, many laws are enforced accepted January 22, 2014. Date of publication March 3, 2014; date of current version August 23, 2016. This work was supported in part by the National to regulate the promotion activities of the tobacco industry. Basic Research Program of China under Grant 2012CB316400; by the National In addition, many social media services (e.g., Facebook and Natural Science Foundation of China under Grants (71103180, 91124001, YouTube) have policies that outlaw the promotion of tobacco 71025001, 91024030, 61332005, 61373119, 61222209, 71272236); by the Beijing Natural Science Foundation under grant 4132072; and by the Doctorate products on their advertising networks. For YouTube, users are Foundation of Northwestern Polytechnical University. allowed to flag “inappropriate” videos. It is undeniable that Y. Liang is with the School of Computer Science and Technology, North- western Polytechnical University, Xi’an 710072, China, and also with the De- participatory media is becoming the new battlefield for tobacco partment of Management Information Systems, Eller College of Management, wars. University of Arizona, Tucson, AZ 85721-0108 USA (e-mail: liangyunji@ With the progress of tobacco wars on participatory media, gmail.com). X. Zhou, B. Guo, and Z. Yu are with the School of Computer Science the seamless monitoring of user interaction on tobacco-related and Technology, Northwestern Polytechnical University, Xi’an 710072, China content is vitally important to properly assess the current (e-mail: [email protected]; [email protected]; [email protected]). situation, the potential risks, and what kind of countermea- D. D. Zeng is with the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, sures has to be taken. However, the following reasons pose Beijing 100190, China, and also with the Department of Management Informa- challenges in characterizing the user interaction on tobacco- tion Systems, Eller College of Management, University of Arizona, Arizona, oriented participatory media. First, large-scale tobacco-related AZ 85721-0108 USA. X. Zheng is with the State Key Laboratory of Management and Control data sets are not available. The existing studies mainly rely on for Complex Systems, Institute of Automation, Chinese Academy of Sciences user survey, and manual data extraction based on questionnaires (CASIA), Beijing 100190, China, and also with the Dongguan Research is time- and labor-consuming. Second, most existing studies Institute of CASIA, Cloud Computing Center, Chinese Academy of Sciences, Dongguan 523808, China. are case studies, and there is a lack of quantification methods. Digital Object Identifier 10.1109/JSYST.2014.2304706 Manual content analysis remains the most common method 1937-9234 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 1194 IEEE SYSTEMS JOURNAL, VOL. 10, NO. 3, SEPTEMBER 2016 used to analyze the social media content by the tobacco control Meanwhile, the connected sensing devices integrated the web community. This approach obviously will not scale when facing and sensing technologies together to extend the ecosystem the exploding social media “big data.” of smart objects and to extract intelligence and knowledge To address those questions, we propose an online tobacco leveraging the interaction of human and objects [4]. surveillance system (OTSS) to automatically collect tobacco- IoT could be applied to many application areas, such as related content data from participatory media and to investigate healthcare, urban planning, and real-world search. For health- the user interaction on tobacco-related participatory media. care, many sensors are utilized to enhance the sensing capa- Although a global tobacco surveillance system (GTSS) is devel- bility and to provide proactive services for users. Chen et al. oped and maintained to collect data on the tobacco use among [5] elaborated a knowledge-driven system to detect fine-grained adults and adolescents1, the data are manually extracted based daily activities with radio-frequency identification tags. For on questionnaires, which is time-consuming and extremely elder adults, a smart home prototype was implemented to costly. Different from a GTSS, an OTSS makes full use of overcome the barriers due to cognitive decline, particularly the data in the tobacco-related participatory media, including memory, hearing, and visual impairment [6], [7]. For urban structured data (such as social relationship) and unstructured planning, a number of studies have extracted citywide human data (such as textual data). Based on the multidimensional mobility patterns using the large-scale data from smart vehicles data in participatory media, many far-reaching studies could and mobile phones. The Real Time Rome project of the Mas- be conducted, including solutions to inhibit/boost the spread of sachusetts Institute of Technology, Cambrige, MA, USA, uses protobacco/antitobacco messages based on topology analysis, the aggregated data from buses and taxis to better understand the evaluation of tobacco policies based on textual data, and the urban dynamics in real time [8]. investigation about the marketing strategies in the protobacco community. B. Collective Activities From Participatory Media The main contributions of this paper are twofold. First, the framework of an OTSS is proposed, through which large-scale Participatory media can be also regarded as a social sensor data sets could be extracted from the tobacco-related participa- in IoT for the analysis of collective activities. For emergencies, tory media. Specifically, a prototype system is implemented to Twitter has been reported to support the real-time mining of capture the tobacco-related data sets from Facebook. To the best natural disasters such as earthquakes [9] and to uncover unusual of our knowledge, it is the first prototype system to automati- regional social activities, such as sports games, thunderstorm, cally collect large-scale tobacco-related data from participatory and fireworks festivals [10]. For social activities, the textual media. Second, we explore the collective interaction to find data in participatory media are utilized to predict political the differences
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