Behavior Informatics: a New Perspective

TRENDS & CONTROVERSIES Editors: longbing Cao, University of Technology, Sydney, [email protected]

Behavior Informatics: A New Perspective

Longbing Cao, University of Technology, Sydney

ehavior is a concept increasingly recognized social and collaborative searching activities is in broad communities spreading from social needed. Gabriella Pasi presents insights on engaging B behaviors in information seeking, especially consid- to business, online, mobile, economic, and cultural ering coupled behaviors within certain contexts. domains. However, systematic and comprehensive Nowadays, an increasing number of users are inter- methodologies, theories, tools, and systems aren’t ested in IPTV programs online, and generate massive ready for deeply, fully, and effectively capturing, amounts of activities. Ya Zhang and her colleagues representing, quantifying, analyzing, learning, and lead a discussion about the behaviors of IPTV users measuring the semantics, sequencing, networking, that are related to system effi ciency, personalization, evolution, utility and impact of individual, group, recommendation, and targeted advertisement. and cohort behaviors taking place in the real world. Finally, Edoardo Serra and V.S. Subrahmanian This is becoming fundamental and critical in the raise an interesting question: Should behavior mod- age of Big Data. Here, in this installment of “Trends els of terror groups be disclosed? They share their & Controversies,” we look at how behavior infor- research and arguments on strategic disclosures and matics targets the development of effective method- consequences in tackling today’s terrorism. ologies and techniques to tackle these issues.

In This Issue To delve into the state of the fi eld, Thorsten The seven selected articles paint a snapshot and Joachims and I present a high-level overview of re- trigger wide discussions about current behavior in- search on behavior computing, discussing deep be- formatics research and applications on diverse issues havior intelligence from a disciplinary perspective. and in different domains. This Trends & Contro- Then, more specifi cally, Can Wang and her col- versies installment hopefully discloses the necessity, leagues discuss the representation, modeling, anal- challenges, prospects, and opportunities for the ysis, and reasoning of coupled group behaviors, in deep, broad, and quantitative development and un- which behaviors share different levels and types derstanding of complex behaviors in the increas- of coupling relationships, as usually seen in social ingly sophisticated real world. networks and community analysis. Social media involves massive crowds of indi- longbing Cao is the director of the Advanced Analytics viduals from different walks of life and generates Institute and a professor in the Faculty of Engineering and an unprecedented scale of behaviors. In looking at IT at the University of Technology, Sydney. Contact him at these behaviors more closely, Reza Zafarani leads [email protected]. a discussion about both individual and collective behaviors in such social media. Effective recommendation is becoming an in- Behavior Computing creasingly important online and social behavior. Guandong Xu and Zhiang Wu share their view on Longbing Cao, University of Technology, Sydney a topical issue—to involve, consolidate, and eval- Thorsten Joachims, Cornell University uate group preference for more targeted group- based recommendation. Behavior is an increasingly important concept in Web search requests are more personalized and the scientifi c, societal, economic, cultural, political, a context-aware understanding of information and military, living, and virtual world. In the dictionary,

IS-29-04-Trends.indd 2 26/08/14 8:06 PM “behavior” refers to a manner of behav- price, and volume on a target secu- • Status (u)—where a behavior is ing or acting, and the action or reaction rity. The actions, response, or presen- currently located; for instance, sta- of any material under given circum- tation, and the effect associated with tus may refer to passive (not trig- stances. In Wikipedia, “behavior” refers the corresponding properties forms a gered), active (triggered, but not to the actions and mannerisms made by concrete and rich object—the behav- finished yet), or done (finished); in organisms, systems, or artificial entities ior of an individual or a group. some other cases, status may in- in conjunction with its environment, Behavior as a computational concept1 clude valid or invalid. which includes the other systems or or- captures major aspects, including the • Associate (m)—other behavior in- ganisms around, as well as the physi- following: demographics of behavioral stances or sequences of actions that cal environment. It’s the response of the subjects and objects; social relationships are associated with the target one; be- system or organism to various stimuli or norms governing the interactions behavior associates may exist because a or inputs—whether internal or external, tween behaviors of an individual or a behavior has an impact on another conscious or subconscious, overt or co- group; behavior sequences or networks or behaviors are related through in- vert, and voluntary or involuntary. and their dynamics; and impact or ef- teraction and business processes to Thus, behavior is ubiquitous and fect generated by the behaviors on sub- form a behavior network. very social. In addition to the common jects and/or objects. Accordingly, an terms, such as consumer behaviors, hu- abstract and generic concept of behav- Accordingly, a behavior instance man behaviors, animal behaviors, and ior (g) may carry (but is not limited to) (g) of an individual or group entity organizational behaviors, behaviors the following attributes and properties: can be represented in terms of a be- appear everywhere at any time. Behav- havior vector →g as follows: iors in the physical world are explicit, • Subject (s)—the entity (or entities) and have been studied from many dif- that issues the activity or activity →g = {s, o, e, g, b, a, l, f, c, t, w, u, m}. ferent aspects. With the rapid devel- sequence. (1) opment and deep engagement of so- • Object (o)—the entity (or entities) cial and digitalized life with advanced on which a behavior is imposed. Further, the behaviors of an individ- computing technology, in particular, • Context (e)—the environment in ual or group form a behavior sequence social networks, social media, online which a behavior is operated, in- G that can be represented in terms of a games, mobile applications, virtual re- cluding the pre-condition and post- vector sequence →Γ, in which behav- ality, multimedia information process- condition of a behavior. iors are connected in terms of social ing, visualization, machine learning, • Goal (g)—the objectives that the relationships R, and pattern recognition, more behav- behavior subject would like to ac- iors in the virtual and social world are complish or bring about. →Γ = R{γ→1, γ→2, ..., γ→n}. (2) emerging. In addition, behaviors in tra- • Belief (b)—belief represents the in- ditional spheres are becoming increas- formational state and knowledge of With the vector-based behavior se- ingly complex with the involvement in the behavior subject about the world. quences, further analysis on such vec- and marriage of the virtual and social • Action (a)—what the behavior sub- tors can identify vector-oriented behav- world. Socio-behaviors dominate these ject has chosen to do or operate. ior patterns. Compared to traditional areas. Behaviors in more classic ar- • Plan (l)—the sequences of actions that sequential pattern mining, such vector- eas—including business, living spaces, a behavior subject can perform to oriented behavior pattern analysis is economics and politics—are also be- achieve one or more of its intentions. much more comprehensive. coming more and more social. • Impact (f)—the results led by the In different applications and sce- execution of a behavior on its ob- Computing Behaviors narios, behaviors present respective ject or context. Existing management information sys- social and non-social characteris- • Constraint (c)—what conditions tems and enterprise applications don’t tics, relationships, structures, and ef- are imposed on the behavior; con- support the storage of behaviors very fects. For instance, in stock markets, straints are instantiated into spe- well. The entity of physical or so- a trader’s behavior influences oth- cific factors in a domain. cial behavior is usually decomposed ers and is embodied through trading • Time (t)—when the behavior occurs. to multiple transactions without pro- actions and action properties, such as • Place (w)—where the behavior tecting the semantics and complete placing a buy quote at a certain time, happens. behavior journey. Behavior as a very

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IS-29-04-Trends.indd 3 26/08/14 8:06 PM Behavior-oriented decision making and governance

Behavior presentation and management also provides a unified mechanism for describing and presenting behavioral elements, behavioral impact, Behavior reasoning Measurement & evaluation and patterns. Behavior Behavior Behavior Behavior • Analyzing behavioral impact. In ana- model checking pattern analysis intent analysis impact analysis lyzing behavioral data, a person might Behavior Behavior

& reasoning Behavior representation be particularly interested in those be-

Behavioral data Source data learning & mining representation havioral instances that are associated with a high impact on business pro- Behavior-relevant applications & domains cesses and/or outcomes. Behavioral impact analysis4,5 features the model- Figure 1. Behavior computing research map. Behavior informatics consists of two ing of behavioral impact. major research directions: behavior representation and reasoning to formalize • Discovering behavioral patterns. behaviors, and behavior learning and mining to analyze behaviors. There are in general two methods of behavioral pattern analysis. One is to soft buzzword is used widely without behavioral impacts,4 and forming and discover behavioral patterns without a clear definition and systematic repre- decomposing behavior-oriented groups consideration of the behavioral im- sentation. Such “implicit” behavior in and collective intelligence for the emer- pact, the other is to analyze the rela- transactional data isn’t consistent with gence of deep behavioral intelligence in tionships between behavior sequences the “explicit” semantic existence in conjunction with their environments. and particular types of impact. business. Hence, it’s necessary and cru- Behavior computing contributes to the • Emerging behavioral intelligence. cial to develop computing techniques in-depth understanding, discovery, ap- To understand behavioral impact for explicit and in-depth quantification plications, services, and management of and patterns, it’s important to scru- and informatics of behaviors. behavior intelligence. tinize behavioral occurrences, evo- With the concept of behavior and In more detail, behavior computing lution, and life cycles, as well as the introduction of an abstract behav- addresses the following key aspects the impact of particular behavioral ior model, the representation, model- (as Figure 1 shows). rules and patterns on behavioral ing, data analysis and mining, learning, evolution and intelligence emer- and decision making of behaviors is be- • Extracting behavioral data. In pre- gence. An important task in becoming doable and increasingly useful, paring behavioral data, behavioral havioral modeling is to define and essential, yet challenging in ubiquitous elements hidden or dispersed in model behavioral rules, protocols, behavioral applications and problem- transactional data must be extracted and relationships, and their impact solving. They form a new computing and connected, and further converted on behavioral evolution and intelli- opportunity, necessity, and technology and mapped into a behavior-oriented gence emergence. innovation, which we refer to as be- feature space, called a behavioral • Understanding behavioral network- havior computing or behavior infor- feature space. In the behavioral fea- ing. Multiple sources of behavior matics2,3 for the explicit and in-depth ture space, behavioral elements are may form into a certain behavioral understanding and analysis of genuine presented into behavioral item sets. network. Particular human behav- behavior-oriented actions, operations, Hence, it’s necessary to map and ior is normally embedded into such a and events associated with many chal- convert transactional data to behav- network to fulfill its roles andeffects lenging business problems. ioral data. in a particular situation. Behavioral Behavior computing (or behavior in- • Representing and modeling behav- network analysis aims to understand formatics) consists of methodologies, ior. This involves developing behav- the intrinsic mechanisms inside a net- techniques, and practical tools for ior-oriented specifications for de- work—for instance, behavioral rules, representing, modeling, analyzing, learn- scribing behavioral elements and the interaction protocols, convergence ing, discovering, and utilizing human, or- relationships among the elements. and divergence of associated behav- ganismal, organizational, societal, arti- The specifications reshape the be- ioral item sets, as well as their effects ficial, and virtual behaviors, behavioral havioral elements to suit the presen- such as network topological struc- interactions and relationships, behavioral tation and construction of behav- tures, linkage relationships, and im- networks, behavioral patterns, and ioral sequences. Behavioral modeling pact dynamics.

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IS-29-04-Trends.indd 4 26/08/14 8:06 PM Fundamental technologies

• Simulating behaviors. To understand y y all of the aforementioned mecha- ... nisms that may exist in behavioral Supporting data, simulation can play an impor- techniques and tools tant role to observing the dynamics, analysis Social network Formal methods

the impact of rules/protocols/pat- System simulations Organizational theor Knowledge discover terns, behavioral intelligence emergence, and the formation and dynam- ... ics of a social behavioral network. • Presenting behaviors. From analyti- Theoretical foundation Logic Visualization

cal and business intelligence perspec- Sequence analysis Multiagent systems tives, behavioral presentation aims to Cause-effect analysis ... explore the presentation means and tools that can effectively describe the motivation and interest of stakehold- Field structure: Mathematics

ers on the particular behavioral data. Social sciences Behavior informatics Systems sciences Cognitive sciences Intelligence sciences In addition to the traditional presen- Information sciences tation of patterns (such as associa- tions), visual behavioral presentation is a major research topic. It’s of high Figure 2. Behavior computing field structure. Behavior informatics, as a research interest to analyze behavioral pat- field, delves into three directions: theoretical foundations, fundamental technologies, and supporting techniques and tools. terns in a visual manner.

These tasks form a clear field struc- gain that can’t be achieved solely by • effectively capturing and quantify- ture and research map of behavior com- usually recorded transactional data. The ing the relationships between be- puting. A generic process of computing deep values and prospects from comput- haviors, behavior evolution, and behaviors will complement classic ap- ing behaviors may be through their impacts, as well as measuring proaches toward a more comprehensive the impact and performance of be- and in-depth behavior understanding • fully disclosing and utilizing the haviors and behavior dynamics on and problem solving. Given a business behavior semantics that are usu- business objectives; application, it first converts entity rela- ally destroyed in recorded transac- • deeply understanding the belief, de- tionship-oriented transactional data to tions and overlooked in behavior sire, and intent behind behaviors behavior feature-oriented data through analysis; conducted and the impact caused; behavior modeling. Behavior patterns, • fully and deeply exploring the be- and exceptions, dynamics, and impacts havior sequences and behavior ma- • actively detecting, early predicting, are then analyzed through developing trix of an actor or a group along a and intervening in unexpected be- corresponding behavior-based analytic certain time period, in which behaviors of individuals, groups, or and learning methods. The outcomes havior properties are involved; cohorts so as to convert them to the are then presented as behavior patterns, • deeply engaging in and learning expected directions and impact. rules, or visual diagrams, and/or trans- about the explicit and (especially formed into decision-support business hidden) social relationships gov- To access these prospects, cross-disci- rules to disclose the interior driving erning behavior formation, struc- plinary efforts are needed. In addition forces and causes of business problems turing, networking, evolution, and to informatics and analytics, theories, and impact. emergence of behavior intelligence; methodologies, and tools available in • deeply discovering behavior pat- statistics, mathematics, econometrics, Prospects and Opportunities terns, exceptions, relational pat- marketing, psychologies, social science, Behavior is becoming an increasingly terns, and changes of individuals, behavior science, behavior finance, and important asset to be deeply analyzed groups, or the global population so on are necessary. This requires col- and understood to disclose its explicit against behavior formation, evolu- laboration between disciplines and and implicit business value and semantic tion, and revolution; cross-domain experts (see Figure 2).

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IS-29-04-Trends.indd 5 26/08/14 8:06 PM There exist unlimited opportunities Coupled Behavior real-world applications, group behav- in deep behavior computing in terms Representation, ior interactions (that is, coupled behav- of complementing the existing be- Modeling, Analysis, and iors) are widely seen in natural, social, havior analysis, data analysis, event Reasoning and artificial behavior-related prob- detection, behavior economics, and lems. Complex behavior and social ap- cognitive study towards data-driven, Can Wang, Commonwealth Scientific plications often exhibit strong explicit semantics-oriented and process-based and Industrial Research Organization or implicit coupling relationships both quantification and formalization of (CSIRO), Australia between their entities and properties. what exactly takes place in the real Longbing Cao, University of Moreover, it’s also quite difficult to world. Many application areas2,3 from Technology, Sydney model, analyze, and check behaviors traditional to emergent issues can ben- Eric Gaussier, University of coupled with one another due to the efit from it; for instance, exploring the Joseph Fourier, complexity from data, domain, con- patterns, anomalies, sequencing of, Jinjiu Li, Yuming Ou, and Dan Luo, text, and impact perspectives. and intent driving customer behav- University of Technology, Sydney Due to the emerging popularity and iors in retail and online shopping busi- importance of coupled behaviors, the nesses, Web usage, and interactions in Behavior refers to the action, reaction, representation, modeling, analysis, the Internet, trading behaviors in capi- or property of an entity, human or oth- mining and learning, and determina- tal markets, and exceptional activities erwise, to situations or stimuli in its tion of coupled behaviors are becoming captured on surveillance systems. environment.1 The in-depth analysis increasingly essential yet challenging of behavior has been increasingly rec- in ubiquitous behavioral applications References ognized as a crucial means for under- and problem-solving techniques. They 1. L. Cao, “In-Depth Behavior Understand- standing and disclosing interior driv- inevitably and undoubtedly constitute ing and Use: The Behavior Informatics ing forces and intrinsic cause-effects new computing opportunities and tech- Approach,” Information Science, vol. on business and social applications, nological innovations, and thus we re- 180, no. 17, 2010, pp. 3067–3085. including Web community analysis, fer to them as coupled behavior infor- 2. L. Cao et al., eds., Behavior and Social counter-terrorism, fraud detection, matics, which is an important branch Computing, LNCS 8178, Springer, 2013. and customer relationship manage- of behavior computing and analytics.4 3. L. Cao and P.S. Yu, eds., Behavior ment. With the deepening and widen- Coupled behavior informatics con- Computing: Modeling, Analysis, Min- ing of social/business intelligences and sists of methodologies, techniques, ing and Decision, Springer, 2012. their networking, the concept of be- and practical tools for exploring hu- 4. L. Cao, Y. Zhao, and C. Zhang, “Mining havior is in great demand to be con- man, organizational, artificial/virtual, Impact-Targeted Activity Patterns in solidated and formalized to deeply qualitative, and quantitative behaviors, Imbalanced Data, IEEE Trans. Knowl- scrutinize the native behavior inten- their interactions and relationships, the edge and Data Eng., vol. 20, no. 8, 2008, tion, lifecycle, and impact on complex formation and decomposition of be- pp. 1053–1066. problems and business issues. havior-oriented groups, and collective 5. L. Cao, Y. Ou, and P.S. Yu, “Coupled Although there’s an emerging focus intelligence. Behavior Analysis with Applications,” on deep behavior studies, such as so- Here, we present the limitations IEEE Trans. Knowledge and Data Eng., cial network analysis,2 periodic behav- of current research, and explore the vol. 24, no. 8, 2012, pp. 1378–1392. ior analysis3 and behavior informatics needs, opportunities, challenges, pros- approach,1 previous research work has pects, and trends of coupled behavior Longbing Cao is the director of the Ad- mainly focused on individual behaviors informatics in terms of coupled be- vanced Analytics Institute and a professor without considering the interactions of havior representation and modeling as in the Faculty of Engineering and IT at the them. However, with increasing net- well as analysis and reasoning. University of Technology, Sydney. Contact work and community-based events him at [email protected]. as well as their applications, such as Coupled Behavior group-based crime and social network Representation and Thorsten Joachims a professor in the De- interactions, coupling relationships be- Modeling partment of Computer Science and in the De- tween behaviors contribute to the in- Coupled behavior representation re- partment of Information Science at Cornell trinsic causes and impacts of eventual fers to develop representation and University. Contact him at [email protected]. business and social problems. In the modeling mechanisms, languages, and

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IS-29-04-Trends.indd 6 26/08/14 8:06 PM tools to capture behavior characteris- which often aren’t obvious and exhibit worth investigating, which include tics, intrinsic and contextual proper- large complexities. However, a deep but are not limited to the following ties of behaviors, behavior dynamics, exploration of interactive relation- points: and internal and external communica- ships is necessary for us to understand tions among behaviors.5 Those tech- how behaviors are correlated and how • How can we define a unified con- niques and methods can also be used those coupled behaviors drive and im- cept of behavior? How can we de- to understand interaction, causality, pact business and social problems. fine a unified concept of coupled convergence, divergence, selection, Group behavior interactions, such behaviors? decision, evolution, emergence, and as multi-robot teamwork and group • What is a coupling relationship? intelligence of behavior entities, be- communications in social networks, How do we qualify and quantify havior properties, behavior networks, are widely seen in both natural, social, the couplings or interactions among and behavior impact. Both formal and and artificial behavior-related applica- a range of behaviors? visual specifications can be discussed tions. Behavior interactions in a group • What kinds of basic coupling rela- to represent coupled behaviors and are often associated with varying cou- tionships can we use to represent behavior interactions. pling relationships—for instance, con- complex interactions among ho- junction or disjunction. Such coupling mogeneous and/or heterogeneous Limitations and Challenges relationships challenge existing behav- behaviors? Existing behavior modeling approaches ior representation methods, because • How do we model coupled behave too many styles and forms ac- they involve multiple behaviors from haviors in both visual and formal cording to distinct situations. There’s different actors, constraints on the in- manners? How do we establish a very limited research on formalizing teractions, and behavior evolution. reversible and unique mapping or the concept of behavior and its ele- link between these two types of ments, which is too weak to reveal that Research Objectives and Issues representation? behavior plays the key role of an inter- Based on the aforementioned limita- • What are respectively the syntac- nal driving force for social and business tions and challenges, coupled behavior tic and semantic interpretations of activities. Additionally, it’s ineffective or representation and modeling is to de- coupled behaviors? What is the re- even impossible to deeply tease out na- velop behavior-oriented specifications lationship between them? tive behavior intention and impact on and formalizations to describe coupled • How can we represent and abstract complex issues and business problems. behaviors (that is, behaviors from ei- behavior interaction patterns? There are no formal behavior repre- ther the same or different actors are sentation models stated from a gen- often coupled with each other) and the Addressing these issues raises oppor- eral perspective and providing a com- relationships among them. It provides tunities for further analysis and rea- prehensive understanding of behavior a unified and formalized mechanism soning of coupled behaviors, which constitution. for describing, presenting, and aggre- are widely seen in community and so- In addition, state-of-the-art research gating behavior interactions, desired cial networks. work doesn’t explicitly model and an- requirements or properties, behavior alyze complex interactions of group impact, and patterns. Coupled Behavior Analysis behaviors directly. Complex cou- Several classical theories and tech- and Reasoning pling relationships between behaviors niques are closely relevant to coupled Coupled behavior analysis and rea- are often ignored or only weakly ad- behavior representation and mod- soning denote proposing effective dressed. Yet these behaviors are often eling, such as ontology, knowledge methods, techniques, and tools for observed to be correlated in terms of representation, software engineering, emergent areas and domains in an- certain coupling relationships—for in- cognition, agent, logic, and matrix alyzing and reasoning about cou- stance, serial or parallel, conjunction computing. By taking great advantage pled behaviors and their properties.1 or disjunction. Such coupling relation- of those underpinning mechanisms, Model checking technique is utilized ships greatly challenge existing behav- the representation and modeling of to verify the coupled behavior model ior representation methods, since they coupled behaviors can be proposed, with desired requirements, and to involve multiple behaviors from differ- designed, and constructed in a solid further refine the model. Coupled ent actors, and add constraints on the and systematical way. During this similarities are also introduced to interactions and behavior evolution, process, a lot of research issues are characterize the quantitative behavior

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IS-29-04-Trends.indd 7 26/08/14 8:06 PM Individual Coupled

Behavior analysis and reasoning, which are used Behavior to analyze, check, and verify complex veriﬁcation reasoning behavioral elements, relationships, ag- gregations, properties, and constraints. It accordingly refines sensitive and problematic model proposals, and then Behavior Behavior Behavior guarantees the robustness and stabil- representation integration algebra ity of coupled behavior representation schemes. Likewise, strategies and theories including action reasoning and composi- tion, the belief-desire-intention model, Behavior Behavior situation calculus, behavior composi- learning evaluation tions, logic reasoning, and model checking have been proposed to analyze and reason about behaviors as well as their interactions. From the perspective of Figure 3. Research issues on coupled behavior informatics. Coupled behavior coupled behavior analysis and reason- informatics aims to build systematic tools to address aspects and issues associated with individuals and groups with coupling relationships. ing, there are many opportunities for us to widely explore. Many open issues are worth widely addressing and sys- interactions in terms of coupling re- but on behavior exterior such as ser- tematically investigating. These inter- lationships between properties (such vice usage. The behavior implication esting research points include but are as attributes, features, and variables) in transactional data also determines not limited to the following: and/or entities (such as objects, re- that it fails to scrutinize behavioral in- cords, and observations). Algorithms tention and the impact on business ap- • The context of coupled behav- and case studies are discussed to an- pearance and applications. iors is to be formalized to control alyze behaviors correlated with one On the other hand, current research the whole process of coupled be- another based on mixed properties often overlooks the checking of behavior analysis and reasoning ac- and complex coupled interactions. havior modeling, which weakens the cording to different requirements. The analytical results will be used for soundness and robustness of models More types of consolidated cou- detection, prediction, intervention, built for complex behavior applica- pling are to be explored and stud- and grouping of coupled behaviors as tions. The quality of behavior inter- ied, and the soft computing tech- well as their interactive relationships. actions aren’t checked through verifi- niques can be adopted to propose cation techniques. Little related work the fuzzy or rough coupled behav- Limitations and Challenges is ready for the formalization and ior informatics. On one hand, traditional behavior verification of coupled behaviors, in- • Analytical problems such as the analysis is usually built on customer cluding elaborating and representing convergence or divergence of cou- demographics and business usage-re- behavioral elements, specifying be- pled behavior vectors are to lated transactions directly. It mainly havior-interactive relationships, and be defined and intensively stud- relies on implicit behavior and explicit checking the modeling of multiple be- ied. Limits of converged coupled business appearance from behavioral havior couplings. The engagement of behavior sequences are to be clari- and social sciences, often leading to in- verification in behavior analysis may fied, which are essential to calculus effective and limited analysis in under- make the findings much more stable and can be used to define continu- standing business and social activities and robust for problem solving. ity, derivatives and integrals. deeply and accurately. With behavior • Some other research issues, includ- implied in demographic and transac- Research Objectives and Issues ing how to define the bases and ditional data, it’s not possible to support With the formal representation of cou- mension of such a coupled behavior in-depth analysis on behavior interior pled behaviors, the coupled behavior space, how to do the space decom- surrounded by behavioral elements, analytics addresses the task of behavior position, how to conduct the linear

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IS-29-04-Trends.indd 8 26/08/14 8:06 PM and nonlinear transformations, are 3. L. Cao, Y. Ou, and P. Yu, “Coupled to exhibit different behaviors such as to be addressed and deeply explored. Behavior Analysis with Applications,” sharing, posting, liking, commenting, • How can we use logic-related repre- IEEE Trans. Knowledge and Data Eng., and befriending conveniently and on sentations to reason about coupled vol. 24, no. 8, 2012, pp. 1378–1392. a daily basis. By carefully analyzing behaviors and their interactions? 4. L. Cao and S.Y. Philip, Behavior Com- behaviors observed on social media, How can we adopt verification tech- puting: Modeling, Analysis, Mining we can categorize these behaviors into niques to check the validity of cou- and Decision, Springer, 2012. individual and collective behavior. In- pled behaviors via certain proper- 5. C. Wang and L. Cao, “Modeling and dividual behavior is exhibited by a ties? How can we extract rules and Analysis of Social Activity Process,” single user, whereas collective behav- mine patterns from analyzing and Behavior Computing, 2012, pp. 21–35. ior is observed when a group of users reasoning about coupled behaviors? behave together. For instance, users Can Wang is a postdoctoral fellow with using the same hashtag on Twitter or As a result of exploring these research Commonwealth Scientific and Industrial migrating to another social media site issues, we’re able to develop a deeper Research Organization (CSIRO), Australia. are examples of collective behavior. understanding of behaviors, especially Contact her at [email protected]. User activities on social media gener- coupled behaviors of interested groups. ate behavioral data, which is massive, Longbing Cao is the director of the Ad- expansive, and indicative of user pref- vanced Analytics Institute and a professor erences, interests, opinions, and rela- in the Faculty of Engineering and IT at the tionships. This behavioral data pro- Based on these discussions, we sum- University of Technology, Sydney. Contact vides a new lens through which we marize the associated research issues him at [email protected]. can observe and analyze individual for coupled behavior informatics (see and collective behaviors of users. Figure 3). Here, we mainly focus on Eric Gaussier is a full professor in computer The scale and existence of this new coupled behavior representation, cou- science at the University of Joseph Fourier. type of data presents behavior analysis pled behavior reasoning, and coupled Contact him at [email protected]. on social media with new challenges. We behavior verification. In fact, these detail first what individual and collective points are designed for qualitative Jinjiu Li is a lecturer in the Advanced Analytics behavior analysis is, and then outline coupled behaviors, which are qualified Institute and at the University of Technology, novel challenges with future work. by actions. Alternatively, some coupled Sydney. Contact him at [email protected]. behaviors are quantified by properties, Individual Behavior Analysis called quantitative coupled behaviors. Yuming Ou is a lecturer in the Advanced Individual behavior can be consid- Accordingly, coupled behavior learn- Analytics Institute and at the University of ered one of the following: ing and coupled behavior evaluation Technology, Sydney. Contact him at yum- are proposed for the quantitative cou- [email protected]. • User-user behavior. This type of pled behaviors. Finally, a coupled be- behavior is observed between two havior algebra can be introduced to Dan Luo is a research fellow in the Ad- users. For example, befriending integrate the qualitative coupled be- vanced Analytics Institute and at the Uni- and following in social media are haviors and quantitative coupled be- versity of Technology, Sydney. Contact her examples of such behavior. haviors, which forms a big picture for at [email protected]. • User-entity behavior. This type of coupled behavior informatics. behavior is exhibited with respect to entities on social media (for ex- References Behavior Analysis in ample, user-generated content). For 1. L. Cao, “In-Depth Behavior Understand- Social Media instance, liking a post on Facebook ing and Use: The Behavior Informatics or posting a tweet on Twitter are Approach,” Information Sciences, vol. Reza Zafarani and Huan Liu, Arizona examples of user-entity behavior. 180, no. 17, 2010, pp. 3067–3085. State University • User-community behavior. This is 2. T. Hogg and G. Szabo, “Diversity the type of behavior that users ex- of Online Community Activities,” With the rise of social media, informa- hibit with respect to communities. Proc. 19th ACM Conf. Hypertext and tion sharing has been democratized. As Joining and leaving communities are Hypermedia , 2008, pp. 227–228. a result, users are given opportunities examples of this type of behavior.

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