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Actor Models and Digital Natives

An Empiric Research Approach for Online Communities

Masterarbeit 2010 110 Seiten

Soziologie - Medien, Kunst, Musik


List of content:

1. Introduction
1.1. Abstract
1.2. Scientific Contribution
1.3. Structure of the Thesis

2. Background
2.1. Motivation
2.2. Scientific Actor Models
2.2.1. Homo Sociologicus
2.2.2. Homo Oeconomicus
2.2.3. Emotional Man
2.3. Current Internet Evolution
2.3.1. Target Group: Digital Natives
2.3.2. Online Communities: Virtual Meeting points and Third Places
2.3.3. Focus Gaming: E-Athletes and professional Gaming

3. Research Framework
3.1. Influence Factors and Operationalization
3.2. Methodology
3.3. Research Approach

4. Analysis
4.1. Social Network and Results
4.2. Explanatory Value of Actor Models in Online Communities
4.3. Comparison of the Explanatory Value within other Virtual Scenarios

5. Discussion

6. Conclusion and Further Work

7. Appendix
7.1. Existing data from previous scientific approaches
7.2. Data for the approach in this thesis

8. Bibliography

List of figures:

Figure 1: Area of conflict for interaction in virtual environments

Figure 2: Overview about the evolution of the number of hosts within the last years

Figure 3: Overview usage of the Internet in 03/2010 along different segments

Figure 4: Critical mass and its effects on the network economy

Figure 5: A classification taxonomy for online communities in the Web 2.0

Figure 6: Examples for marketing with professional e-sport players

Figure 7: Korean e-sport tournament location

Figure 8: The five step verifying pattern for actor model decisions

Figure 9: Overview about the research approach, based on the existing data, two different analysis methods are used (own illustration)

Figure 10: Design of the online gaming community – (cp to

Figure 11: Illustration of the ego-centered network analysis as one of two methods to analyze the virtual interaction for this thesis (own illustration)

Figure 12: Visualization of the overlapping social network between the eight test-subjects (own illustration)

Figure 13: Time graph: Number of subscriptions per day during the experiment period

Figure 14: Overview about the explanatory value of the actor models along the stress field between rational and social influence within the virtual environment (own illustration)

Figure 15: Overview about the methodological framework for a combination and maximization of explanatory value for actor models in a virtual context (own illustration)

1. Introduction

Acting within a social context provides many research opportunities and is currently a major research focus in sociology. The goal is to improve the understanding of the human interaction and its influence factors. In this context actor models provide a causal interconnection between the reason (motivation) and the human (inter-)action itself. From a behavioral perspective it describes the stimulus-reaction causality.

Although not every human behavior can be explained sorely through instinct and drive. At this point the actor models aim to address additional factors for human behavioral motivation. Based on the model, these additional factors can rely in different aspects, such as logic, social pressure or emotional reactions. The main dissociation from biology relies within the abstraction from pure instinct-driven causalities.

Nevertheless the research field of actor models and human interaction shows a clear interdisciplinary focus. The influence from psychology contains the decision and learning aspects of humans within their interaction. Economy furthermore adds a mathematical perspective, which reflects the current importance of the economical system for the whole society (prime system compared to other society systems). Additionally with the mega-trend of virtualization[1], the computer science provides further information about communication and interaction changes through the invention of new technologies. In this interdisciplinary research area the following thesis provides a detailed evaluation about the conceptual feasibility of sociological actor models within virtual environments[2].

1.1. Abstract

This thesis evaluates the role of actor models with regard to the changes in virtual environments. The most commonly used actor models, the homo economicus and the homo sociologicus as well as the emotional man and several less popular models are compared with regard to their level of explanation for behavior in virtual environment. In this context online communities (i.e. gaming communities) are observed.

The research framework and the structural conception of the measurement also are explained in detail. A significant share of the input is based onto qualitative interviews with eight different digital natives, who share a common computer gaming affinity. The analysis includes qualitative interviews with these e-athletes[3] concerning their behavior within online communities. These interviews contain interesting findings about their motivation, especially the difference between virtual and real world social relationships.

The analysis shows interesting results, since the players differentiate in between their role as an e-athlete versus their role as a person. This leads to a multi-causal influence for their behavior, which cannot sorely be explained with a single influence factor. Neither the homo economicus nor the homo sociologicus thus can explain their behavior on its own. Therefore this thesis discusses methods to improve the current models in order to adopt behavioral changes through virtual environments. A trade-off between the most commonly models is given. Afterwards the results of the analysis are compared to the statements of the interview partners. These interviews indicate a strong personal influence from the environment on the role of a private person. Additionally the behavior as an e-athlete is also influenced by logical decisions, which can be modeled through the homo economicus.

1.2. Scientific Contribution

This thesis provides a detailed discussion about the role of the actor models within a rapidly changing society. The influence factor of virtual environments yet is not included in the scientific discussion about motivation and the resulting actor models. Hence this thesis provides first evidence of structural incompatibilities in between the generalized actor models and the motivation-action interconnection within the modern society with a growing focus on virtual interactivities.

The chosen case-study along an online gaming community offers both: Quantitative data of the usage of virtual environments as well as qualitative data from the structured interviews with eight participants. Supplemental guided interviews act as a basis for operationalization for the actor models. The interview partners report in detail about their behavior in virtual environments and their motivational factors.

Within the discussion of the results, the general question whether actor models contribute sufficient exploratory power for human interaction is enriched by the virtual dimension. This additional viewpoint adds a further perspective, since the dynamic of digital interaction is influenced by the communication medium.

The findings of the thesis need to be relativized; only one specific case study yet is observed. In order to improve the reliability, further research in the field of actor models in virtual environments needs to be done. Although gaming offers a typical interaction within the Internet, several other contexts exist. With regard to this limitation, the findings can be perceived as a first evaluation aiming to improve the exploratory power of the existing models.

1.3. Structure of the Thesis

The remaining thesis structures as following:

Chapter 2 provides background information about the related research fields. First, the motivation for the actor models is described. Secondly the most common scientific concepts for actor models, such as the homo economicus and the homo sociologicus are described. The third part of the chapter focuses onto the current state of Internet evolution, including the target group of digital natives, the creation of virtual meeting-points and the research emphasis of e-athletes and virtual sports.

Following Chapter 3 describes the research framework, where the most important influence factors are given. Also a detailed description about the methodology as well as the research approach is drafted.

Chapter 4 contains the analysis of the given data, especially the clustering and evaluation of the interviews. The initial interviews are backed up with further guided interviews (same sample group with additional guided questions regarding the behavior) in order to operationalize the answers within the actor model context. Additional data for the online community scenario is included to dissect the influence of virtual third places onto the individual behavior.

The discussion in Chapter 5 includes a structured analysis about the main findings from the interviews. As a focus two major aspects are discussed in depth:

- The role of the virtual environment (modeled along a given online community) and its influence onto the test-subjects in terms of social interaction and motivation.
- The explanatory power of actor models in a highly individualized society and the additional stress field in between the virtual environment evolution and the young generation of digital natives. How much explanatory power is left?

Finally Chapter 6 concludes the main findings and the discussion indicates current research limitations and outlines further research opportunities.

2. Background

The modern society shows a rapid evolution (caused by technological changes, individual motivation and social interaction) with drastic changes within all living areas for the individuals. Within the last twenty years, the technological evolution was even increasing the pace of this changing environment. The options of digital communication further increased both – the information density and the information speed – hence permanently changing the way that individuals communicate to each other. This change penetrates nearly every social area of the individuals, ranging from the private sector over changes within the workspace even to mass media and politics (including law and the government).

As a result, the interaction in between the individuals of modern society fundamentally changed. With regard to the group of digital natives[4] (Prensky, 2008) a more drastic change is observable. Most of the digital natives not only adopt the Internet and digital communication stage as a part of their lifestyle, rather than relying strongly on it. As an example, a growing number of the current relationships within this age group (born after 1980) are based on contacts of digital social networks (compare to Nauert, 2010). These virtual places are used as interaction spaces and exist on parallel to the real world. Yet their influence is even growing[5].

This chapter contains the background information for the thesis, introducing the motivation to scientifically analyze the changes within the behavior of Internet users. Afterwards the major actor models are described in depth: The homo oeconomicus, homo sociologicus and the emotional man. On par with the introduction of the actor models, a further description of the current digitalization trend[6] is given in order to pinpoint the significance in its influence onto the individual behavior. This introduction includes the group of digital natives, the evolution of online communities and the background information for the focus of this thesis: Professional gaming and e-athletes.

2.1. Motivation

The interdisciplinary problem field of behavior in digital environments has got different motivational factors. From a computer science perspective, the understanding of users’ needs and their motivation enables improved design and functionality for digital communication. These design criteria closely interact with restrictions from the underlying business model, which is highly influenced by the social interaction and preferences. On par with these interdependencies, further connections with a sociological perspective occur. The individuals’ interaction always influences its environment, based on the Georg Simmels interaction theory. He describes the interdependence between the actor and his/her social structure as a relationship of dualism. The individuum is product and producer of its own environment, thus the interdependencies between the individuum and the social structure show a complex bound (compare to Dörr-Backes and Nieder, 1995, S.54ff.). Based onto this interdependence, a fundamental change within the behavior of the individuum implies a following change within the social structure and vice versa. Therefore the rise of the virtual environments will permanently alter the social interaction, at least the interaction within the virtual environment.

The research field of social interaction therefore shows several scientific disciplines, which influence the topic. Figure 1 illustrates the area of conflict between computer science, business administration and sociology for the topic of virtual behavior.

illustration not visible in this excerpt

Figure 1: Area of conflict for interaction in virtual environments

(Own illustration)

With regard towards the motivation of the individuals the change through digitalization also influences existing theories, such as actor models. Generally Schimank (2009) describes two disjunctive sociological problem fields: The reason for the individuum to act (motivation and selection of behavior) and the influence of an actor onto the social structure. The first aspect will be covered intensively within this thesis. Meanwhile the interdependencies with the environments are further complex research fields. Some aspects, like the results in changing behavior for online communities, can be covered within this thesis. The vast amount of remaining topics in this large research field (i.e. other communication media, different target groups, different cultural influence factors, generalization of the findings, validation through retesting or different sampling, etc.) will be out of scope.

The leading question for this thesis will be: What drives individual behavior and how accurate are actor models able to describe these drivers?

The first part of this question indicates that the behavior is based on personal drivers (motivations). Different social models already describe these motivational factors (such as the Heckhausens rubikon-model[7], Maslow’s motivational pyramid[8], Correll's five factor model for basic motivations[9], Deci’s model of intrinsic and extrinsic motivation[10], etc.). Although the sole existence of motivational factors alone does not describe the resulting behavior. In order to close this gap, actor models offer one method to convert the pure motivation into resulting (inter-)action of the individuum. These models therefore interconnect the influence factors with the execution.

This interconnection leads to the second part of the leading research question: How well can actor models describe the individual behavior ? For virtual environments the existing actor models need to be flexible enough to properly include the change within subject’s interaction. This highly depends onto the model and its main influence factors[11]. The described interdependence between the individuum and his/her social structure adopt a significant role. To clarify the explanatory value of actor models within virtual environments, each of the described actor models must be analyzed and compared with regard towards their sturdiness against environmental changes.

2.2. Scientific Actor Models

Actor models describe the reason for the behavior of a subject. In order to describe the most common actor models, it is necessary to define human interaction. Meanwhile human action describes a motive-driven behavior; the behavior itself can be more generalized. One definition within this context from Weber (1922) states: “(…) human behavior can be described as an action (…), if the acting subject interconnects it with a sense” (Weber, 1922, S.5 ff.).

This ‘sense’ is the main connector in between pure motivation and human action. The central pre-assumption for this connection is a causal interdependence between sense and action. If the subject fails to perceive a sense behind its action, then he/she will act on instinct. As a result, the actor models aim to explain the main motivational factors. In other words, they ask for the ‘sense’.

The human action however is not independent from the social environment. As implied within the previous section, social interaction always refers to the context. Thus actor models need to take in account this interdependence to validate them. In the scientific sociological discussion, two major models have been established: The homo oeconomicus describes the acting through a rational maximization of the individual benefit. And the homo sociologicus, which describes human behavior based on role expectations (priorized by the different social areas). Many other actor models expand the basic idea of these two sources of influence. The major difference of the two models implied a long scientific discussion whether the internal influence (homo oeconomicus) or the external influence (homo sociologicus) prevails[12].

An additional actor model, the so called emotional man, is introduced by Helena Flam (2000). It uses the further dimension of emotions as an explanation for human interaction. This dimension differs from purely rational perspective of the homo oeconomicus and offers an additional explanation of internal motivation factors.

All three actor models will be discussed in context to the user group of digital natives and the rising importance of virtual environments. As a sample, the e-athletes represent digital natives with a gaming focus and will act as a case-study for the discussion. Using their example the adoptability of the actor models for virtual examples will be illustrated. The discussion of this thesis will not only compare the individual explanatory value of the three chosen actor models. Furthermore the general discussion, whether actor models appropriately exhibit human interaction will be evaluated with regard to the virtual environment.

2.2.1. Homo Sociologicus

The first described actor model is the homo sociologicus, which is a norm-oriented explanatory model. Its main explanation for individual behavior relies in the social pressure coming from the environment. The actor him-/herself fulfils a role and is therefore bound onto the expectations of others regarding his duties and commitments. These commitments and the motivation to live up to the expectations are the main driver for the individuum in this model.

The original evolution of the homo sociologicus is based on Durkheim (1885, S 105-140), who argues that social norms and their compulsion affect the individual behavior. The main finding of the text is that a subject is significantly influenced by its commitments. Nonconform behavior leads to negative consequences due to social avengement.

Durkheim argues closely along the norms of a family: “If I meet my duties as a brother, a husband or civilian or if I pay my debts, then I obey the commitments outside of my own person and my sphere of will (…)” (Durkheim, 1885, S. 105). In this quote Durkheim underlines that the person follows a normative paradigm and receives impulses, which generate motivation for individual behavior. These impulses however do not arise from inside the ‘own sphere of will’ rather than from the social environment. Nevertheless the person obeys these expectations. By consequently following this logic, the results state that in the long run the subject follows his/her motivation to minimize social conflicts.

From this logic further implications for the homo sociologicus arise:

Firstly the question of the strength of influence through the social environment needs to be addressed. Parson (1971) discusses this aspect and describes the individual behavior of the subject and his/her organization. In his paper the author describes that a selection for (inter-)action always contains a decision against an alternative. This tradeoff between the options includes physical and normative incentives. Based on the situation either side can prevail, the decision finally is strongly depending on the situation.

Secondly the long-term planning for subjects also has got interdependencies with the social environment. Hence spontaneous social contacts show a different role compared to long-term, stabile social connections. This theory is closely linked towards the exchange theory of Thibaut and Kelly (1959)[13] and Kelley (1978). The exchange theory is a social psychological and sociological perspective that explains social change and stability as a process of negotiated exchanges in between parties. It values the social exchange in human relationships as a subjective cost-benefit analysis and the comparison of alternatives by the subject. In respect of long-term planning, the subject thus uses an internal evaluation of the comparison levels between the alternatives and the consequences for nonconform behavior. This automatically leads to the question how different contextual situations can have an influence on this evaluation.

For the homo sociologicus, the explanation for contextual influences uses the construct of ‘roles’. These roles are introduced in Linton (1945) and are related to the movie actor scene. One role in this context is in effect for: “(…) every location with a field of social relation s” (Dahrendorf, 1958, p.141). This quote refers towards the structural integration of roles along the social environment. As an analogy to the quote, a subject (especially in modern societies) is included in different social environments. These environments contain different, in some cases even contraries expectations for the individuum. Depending onto the situation, the homo sociologicus is exposed to a diverse set of exigencies and needs to react accordingly.

Over the years of discussion, three subgroups (versions) of the homo sociologicus have evolved. The first version describes the classic interpretation of the homo sociologicus. Within this version the subject purely aligns the personal behavior along the given values and norms without his/her own value add. In context to the described dualism, such an interpretation ignores the interdependencies with the environment. Version two describes the subject as an actor, who follows only normative regulations, such as internal norms or external sanctions. Thus his/her actions are rather an automatic performance of norm conform behavior. It is often described through the SRSM-model (socialized, role-playing, sanctioned man)[14]. The third version describes the homo sociologicus from an empiric standpoint. The main influence factors rely within the attitudes towards objects and topics. This version is commonly modeled with the OSAM-model (opinionated, sensitive, acting man)[15]. By comparing these three versions, mostly either the SRSM or the OSAM model is used for the motivational explanation of the homo sociologicus. Meanwhile the first version appears to be no longer contemporary due to the interconnection in between subject and environment (dualism). Table 1 gives an overview about the three sub-versions and their different explanations for the behavior of the homo sociologicus.

Table 1: Overview about the three different sub-versions of the homo sociologicus and their explanation (cp. Esser, 1996, pp. 232-233)

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In a general sociological context, the homo sociologicus resumes an outstanding role, obtaining the status of the standard actor model for a long period[16]. In many references, it is part of the ongoing discussion, which actor models should be used for the description of the individual behavior[17] [18] [19]. The main discussion arose between the homo sociologicus and the homo oeconomicus, based on two facts. Both models show completely different approaches towards the actors motivation, meanwhile the homo sociologicus attributes external influence factors to be the main reason for his/her interaction, the homo oeconomicus claims that internal maximization of utility functions are responsible. Furthermore the both models are built on completely different ideas of men.

The main difference in between the motivation of homo sociologicus and the homo oeconomicus in terms of explanatory value is their different approach for the causalities between motivation and action. The homo sociologicus has got a strong external motivation for interaction (based onto the expectations of the social environment). The person itself is therefore driven by its roles and the expectations of others.

For this thesis, the homo sociologicus will act as one of the actor models within the analysis. A crucial part of the explanatory value of this actor model relies in the interaction between subject and environment. Therefore a drastic change within the environment can lead to incompatibility in explaining the model. Especially for virtual environments the change within interaction is drastic. The example of an online community in this thesis will evaluate how well the usage of ‘roles’ fits into the context of virtual interaction.

2.2.2. Homo Oeconomicus

The second major actor model is the homo oeconomicus, which differs in decisive ways from the homo sociologicus. Its explanation for the human behavior relies onto internal motivation and a rational calculation. The basic concept of the model is the description of the human behavior through an internal ‘accounting function’ that describes the personal benefit. A subject, along its planning horizon, has got the motivation to maximize the overall value of this personal benefit.

Through this internal accounting function the homo oeconomicus can be modeled with mathematical methods. The behavior, which is following a simple mathematical maximization, thus can also be modeled through calculation. This fact made the homo oeconomicus the preferred actor model for economic science, including both business administration and economics. Based on this causal interdependence between accounting function for personal benefit and reaction of the subject, plausible explanations for opportunistic behavior (such as the prisoner dilemma[20] ) can be made.

Although the model is widely used in economic science, it also spreads into the sociology. Along with the increasing importance of the economic sector within the society, the homo oeconomicus receives additional importance. The economic sector shows interdependence with all other parts of the society: “(…) the adoption of the physical environment through the society system accents the acquisition of resources and the fulfilling of (personal) needs.” (Deutschmann, 2009, p.49). The quote refers to the fulfilling of personal needs within the subjects action. These needs would be described by the internal accounting function.

The subject’s decision to maximize the personal gain follows a strict rational behavior. As an underlying general principle subjects maximize their gain within their limited objectivity. This limitation is important, since the subject both has got a limited time horizon (through future insecurity) and very limited information (plus a subjective interpretation). In economic science, this limitation is modeled through the marginal curve of indifference, which describes the personal taste and subjective interpretation of the given information. Thus the optimization of the benefit is always an optimization of personal gain. This can be explained though Georg Simmels explanation of trading and exchange: “The reason for exchange: The values sum after the exchange is larger than before the exchange – means that both parts give the trade-partner ‘more’ than one had possessed before trading” (Jung, 1990, p.34)[21]. Such an exchange could only be possible by taking the subjective value of the trading goods.

From the perspective of the motivations origin, the homo oeconomicus differentiates from the ‘role taking’ approach of the homo sociologicus and implies a subject’s motivation for agentic behavior. With regard to the social environment, the homo economicus takes the problem of personal benefit maximization further. Through limited resources (such as time, money, education, etc.) distribution problems in between the subjects of the society exist. As a result, no trivial equilibrium (win/win situation for every subject) exists, which maximizes the personal gain of all subjects. Especially since the personal accounting function can change within the timeframe. New technologies, opportunities or changing demographical factors strongly influence the subject’s behavior. This change would lead to a dynamic, constantly alternating optimum (which realistically cannot be reached).

As a result of the scarce resources and the subjects motivation to maximize their own benefits, inter- and intra-personal conflicts will occur. These conflicts would correspondent to the different motivations, norms and expectations within the homo sociologicus model. For the homo oeconomicus, they offer influence factors for the internal accounting function and the subject calculates the impact for his/her personal gain. In terms of subjective perception, the homo oeconomicus has got limited information, which represents the incompleteness of his/her perception.

In the long run the subject uses the mechanism of discounting, valuing events in the near future over these in a distant future. This effect combines both described aspects from above: The subject is aware of the limited resources and aims to maximize its current benefit. Nevertheless upcoming events (such as an exam) can be predicted and will be taken into the internal calculation the closer this event approaches.

The underlying paradigm for the subject’s actions differs from the approaches shown in the homo sociologicus. Miebach (2010) discusses the different paradigms in order to illustrate the diverse world views in between the actor models. Table 2 gives an overview about the model paradigms for two of the homo sociologicus and the homo oeconomicus. From a paradigm-perspective, the main difference between the models relies in the strong evaluation and maximization approach of the homo oeconomicus.

Table 2: Overview about the three different paradigms for the homo sociologicus and the homo oeconomicus (cp. Miebach, 2010, pp. 30)

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With regard to the virtual environment, the explanation of the homo sociologicus needs to address the different environmental influence factors. Two aspects in particular will significantly alter the explanatory value.

On the one hand the information density and amount of information increases, which leads to a very limited perspective of the individuum compared to the overall amount of available data. This discrepancy can have an influence on the explanation, because the internal function is becoming more complex and the subject will further tend to reduce the information complexity. Maybe no decision though information overload is made.

On the other hand the diversity of environmental influence factors multiplies. The virtual environments (throughout all communication channels like mail, newsgroups, MUDs, chats, twitter, etc.) offer various influences on top to the already social environments. With this increase in influence, the argumentation for a purely internal motivation of the subject will need to explain non-opportunistic, non-rational behavior and obvious social influence as well.

2.2.3. Emotional Man

The last two chapters introduced the homo oeconomicus and the homo sociologicus as the most important role models for the sociology. A further model will be introduced to supplement with another form of explanatory value. Schimank (2009) states: “The emotional man) completes the sociological tool box for explaining the behavioral motivation. The question, which needs to be addressed, is: What are emotions and what is the identity of an actor/subject?” (Schimank, 2009, p.94).

Different sociological authors underline the emotional dimension and its influence on the behavior[22]. The theoretical operationalization from Weber for example differentiates between ‘traditional’ (e.g. life long enviousness) behavior and ‘affect driven’ (e.g. spontaneous enragement) behavior (Weber, 1922, p.12). A considerable difference between the emotions and instincts is that the pure stimulus-reaction sequence is no longer the only explanation for behavior. Instincts purely focus on automatically, hard-wired biological reactions. Meanwhile emotions include a parallel converting of information along the subjects’ values.

The emotional man as an actor model therefore is driven by his/her emotions. Helena Flam (1989) describes this dependence on emotions: “Emotions are supplying the actor with a ghostlike picture of the situation, from which the behavioral choices result.” (Schimank, 2009, p.94)[23]. With the usage of context information, the emotional man shows parallels towards the homo oeconomicus. Their main difference relies in the fact that the emotional man actor model is not relying on an internal optimization function of personal benefit, rather than on emotional closeness towards subjects or situations. As a result, the decision is primarily based on the emotional interdependence rather than rational optimization. In context of the internal/external driver perspective, the emotional man has an internal aspect, since the responsible emotions have got an internal origin[24].

Another similarity exists in between the homo sociologicus and the emotional man. Both are strongly interdependent with their social environment. Meanwhile the homo sociologicus argues that the social role of the subject is mainly responsible for his/her interaction, the cause-reaction chain is somewhat different at the emotional man. The main driver in the emotional man actor models are the internal emotions. These however are based on social relationships; Schimank[25] (2009) describes them as ‘relationship-oriented emotions’. They do affect the subjective perception (e.g. by regarding behavior of a good friend to be much more positive compared to a neutral observation). This interdependence with social relationships widens the influence of the actor model from an internal towards an external influence. Hence the emotional man is not strictly relying on just internal or just external influences.

Regarding the strength of the emotional influence, Flam (1989) describes two different models. Table 3 gives an overview about the major differences in between these versions of the emotional man:

Table 3: Overview about the two different subversions of the emotional man and their differences (cp. Schimank, 2009, p.98ff.)

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As the first sub-category the pure emotional man is introduced. The subject of this actor model is completely driven by his/her emotions. Therefore the subject appears to be unfree, totally guided along the spontaneous emotions, always living to them with full resources (e.g. rage attempts are not partially controlled, rather than appearing in complete strength). This leads to ignorance with regard to the consequences of such behavior. Also the consistency of the emotions is non existent. A subject can have got positive and negative emotions towards a target (e.g. loving and hating a person at the same time). The pure emotional man is a theoretical construct, because no subject would completely neglect the consequences of its own behavior regulars.

As an expansion to the pure emotional man, the constrained emotional man version of the actor model indicates an emotional influence without completely obeying them. Subjects of the constrained emotional man are strongly influenced by emotions, nevertheless they do control them to a certain extend, where they therefore can fulfill role-expectations of their social environment or rational based advantages. This interdependence with other influence factors combines both, the internal and external influence, creating further guidelines along the emotional influence onto the subject. Whenever emotions occur, the subject channels them to fulfill either further internal or external constraints[26]. This interdependence with the other big actor models closes the gap in between the external and the internal motivation, although the major disadvantage relies within the observation of root causes. The stronger a subject is motivated by internal optimization of external role expectancies, the lesser the explanatory value of the emotions as a root driver for the behavior will be.

2.3. Current Internet Evolution

The Internet is based on the effort of a small group of people in the 1960s, who predicted a great potential within the computer based communication (initially based on the ARPA[27] project). As a network, the number of hosts and their usage was very limited and mainly focused on scientific usage at the very beginning. Within the early 1990s, the size of the Internet, along with its content was growing exponentially. The number of hosts[28] rose towards hundreds of millions. This evolution went along with technological trends and developments, such as the installation of routers[29], the definition of technical standards[30], software and language description[31] and intense scientific research within the field of network design[32].

In order to illustrate the rapid growth, figure 2 gives an overview about the number of hosts in the Internet:

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Figure 2: Overview about the evolution of the number of hosts within the last years

(Cp. to Pastor-Satorras and Vespignani, 2009, p.7)

Especially within the last five years the Internet completely changed. Nowadays the Internet coverage grew enormously; More than 1 billion people around the world are already connected. Depending on different underlying statistics, the percentage rate ranges in between 15% and 23.5% of the world population and the proportion is increasing[33]. Both, the technological opportunities as well as the largely growing user communities, changed the classical Internet towards the Web 2.0.

During this time[34] different forms of communication and interaction were generated. The Web 1.0 also known as ‘Information Web’ adhere only a one way communication. Mostly text based interaction within news groups and mailing lists occurred. In contrast the Web 2.0 or ‘Social Web’ enabled a form of many-to-many communication. Especially the social interaction factor therefore completely changed and with the growth of the different communication channels (such as online user communities) the motivation of a virtual interaction changed accordingly. Social online communities like Facebook, StudiVZ or Xing, the micro blogging platform Twitter and various blogs[35] with all kinds of topics are growing daily, offering radically different ways to interact and build new kind of social networks.

The change between the classical communication and the Web 2.0 communication (including future trends of Web 3.0[36] interaction) show that the change within the Internet and thus the change in interaction between the subjects has got acquired a pace like never seen before. As an illustration for the change and the topic structure within the Internet, figure 3 shows an overview about the different topics within the network and their size compared to the overall activities.

The interaction within social networks (such as online communities) has got a large share of the overall digital interaction[37]. Therefore an online community is a representative form of virtual interaction[38]. This section will introduce three different aspects of the shown Internet trend. First, the target group of digital natives is featured. They are a demographic group of young people, who initially grew up with the new opportunities of the Internet.

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Figure 3: Overview usage of the Internet in 03/2010 along different segments.

(Cp. to BBC technology report, 2010)

The digital natives show a difference within their behavior compared to non-digital natives and will be important for the analysis in regard to future interaction evolution. Secondly, the virtual meeting points of online communities are introduced as a typical representative form of digital interaction. Thirdly, as a focus for this thesis, information about the sector of online gaming and professional e-athletes is given. These individuals will act as the sample group for the research approach.

2.3.1. Target Group: Digital Natives

Digital natives are arising along the evolution of the Internet. The rapid growth leads to a sharp cut in between those, who were adapting to the Internet in their adolescence and those, who are ‘growing up’ with the Internet. Within the second group, the adoption of virtual environments, its usage and the possibilities are adopted naturally. The term of digital natives is based on Prensky[39] (2001). He describes the digital natives as: “Our students have changed radically. Today’s students are no longer the people our educational system was designed for. (…) Computer games, email, the Internet, cell phones and instant messaging are integral parts of their lives. (…) it is very likely that our students’ brains have physically changed – and are different from ours – as a result of how they grow up” (Prensky, 2001, p.23).

Prensky mentions many important aspects within his paper. A few of them will also be relevant within this thesis. His relation to the computer for example will be one aspect for the focus selection of our sample group[40]. Furthermore his reference towards the changes in behavior, which also affects the interaction in between the subjects are leading to the research of digital natives. Digital natives behave differently and especially in virtual environments completely new social activities exist.

Another argument is the physical modification of the subjects perception (explained through a change inside the brain), which leads to an expanding of the cognitive capability. Presky states that therefore digital natives are capable of receiving and understanding information faster compared to digital immigrants. Although this difference yet could not be physically proven, indications for a change within the perception of digital natives are frequently discussed[41].

These users do not only grow up with the technological options, they rather take them as a naturally given form of interaction. “For many people, life has added a further important element: The virtual world, which supplements the real world” (Palfrey and Gasser, 2008, p.29). The indicated supplement has got strong influences on the real world and the real behavior as well. One example of this influence is the strength of virtual information about the subject: “(…) Others obviously understood better, which meaning online published information has.” (Palfrey and Gasser, 2008, p.34).

The difference in between the group of digital natives and the digital immigrants relies within their perception of the medium Internet / digital world[42]. Digital natives adopt their virtual environment, since they are born with it and the interconnection appears to be natural. Palfrey and Gasser therefore argue that the digital native phenomenon is not culturally limited, rather than strongly dependent on the age structure[43].

As a result of the change in behavior, digital natives are also topic of the scientific observation. “Digital natives already initiated severe changes – and we only stand at the beginning. Since many more digital natives are reaching adolescence, we will encounter a new level of productivity, customer driven innovation and new platforms of creativity, which are not foresight able yet.” (Palfrey and Gasser, 2008, p.284f.). These innovation trends and behavior within the network are observable at multiple examples. One of theses examples is the growth of online communities, which act as virtual meeting points and so called third places. This aspect is going to be introduced during the next section.

To conclude the excursus, a definition for the target group of digital natives is needed. This thesis therefore uses Frielings explanation of the digital native group: “Digital natives is a term for a generation born after 1980, who grew up with digital medias, such as mobile phones and the Internet and perceive these devices as a natural part of their living environment” (Frieling, 2010, p.32).

2.3.2. Online Communities: Virtual Meeting points and Third Places

One of the digital communication methods is the online community. It differs from the other methods, such as newsgroups, mailing lists, blogs, twitter, MUDs, graphical environments, live chats and instant messengers by building a social framework into a digital environment. Usually a web platform is build around these social frameworks, where the users share a common interest.

Online communities in general show common aspects, in terms of their evolution and critical factors for their success. In order to understand the interaction in between the users and the influence factors for online communities this section covers the relevant aspects and describes, how these communities evolve.

A definition of the term online community can be found in the Encyclopedia Britannica (2010): “An online community is a group of people that primarily interact via some form of mechanism such as letters, telephone, e-mail or Usenet rather than face to face. If the mechanism is a computer network, it is called an online community.

An overview about the definitions for virtual communities can be found in Lee et al. (2003), Hagel and Armstrong (1997) and Jones and Rafaeli (2000). Table 4 features the overview about the most common definitions. These historical definitions show that the inter-personal aspect of online communities was the main definition aspect at first, then ranging to member-generated content and interpersonal interaction. With these four[44] definitions together, a sharper picture can be drawn of what exactly online communities are.

Table 4: Overview about related definitions for virtual (online) communities (cp. Hagel 2006, pp. 61-65)

illustration not visible in this excerpt

As Hagel (2006) explains, the user groups initially had no commercial background, they evolved from news groups. Hagel (2006) explains that user communities are described through five significant attributes:

1) A specific central point of interest (that defines the common focus)
2) The opportunity to integrate content and communication
3) The usage of information that are contributed by the users themselves
4) The access to different competing producers
5) A commercial orientation


[1] For example through the growth of the Internet, the role of the computer in the modern society and the rapid evolution of technology.

[2] Most current virtual environments are primarily visual experiences, displayed either on a computer screen or through special stereoscopic displays, but some simulations include additional sensory information, such as sound through speakers or headphones. Some advanced, haptic systems now include tactile information, generally known as force feedback, in medical and gaming applications.

[3] E-athletes are professional computer gamers, who dedicate a large amount of their time in order to become successful in player-vs-player or player-vs-environment competitions (compare to Fritsch, 2006)

[4] A person, who has learned to interact with the digital medium due his/her childhood experiences, thus adopting the new medium communication methods as natural and given is called digital natives. Usually these individuals are 30 years or younger, because the large boom of the Internet occurred within the late 1990th.

[5] Compare to the number of active users in facebook:!/press/info.php?timeline (last checked 25.05.2010)

[6] The current trend of digitalization contains various communication forms, including chats, email, forums, MUDs, newsgroups, etc. This thesis will mainly focus onto the online communities, because they offer a relatively stable environment and provide a common topic. The results nevertheless need further validation to be generalized for other communication channels.

[7] Compare to Heckhausen and Halisch (1986) and Dörner (2009)

[8] Compare to Kirchler(2008, S.99ff.) and DuBrin (2008, S375ff.)

[9] Compare to Albarracin et al. (2005), Correll (2006) and Correll (2007)

[10] Compare to Schiefele (1993), Thomas (2000)

[11] In example for the homo sociologicus model, which describes the motivation as to be influenced by the expectation of the social environment. A drastical change in this environement, like virtualization, therefore also influences the actors’ motivation.

[12] Compare to the discussion in Schimank (2009, p.141ff.)

[13] Compare to Aronson et al (2008, p.373ff.) and Heinemann (2008)

[14] Compare to Esser (1996, p. 232ff.), Esser (2000) and Miebach (2010, p.29ff.)

[15] Compare to Esser (1996, p.233ff.) and Mayerl (2008, p.32ff.)

[16] Compare to Dahrendorf (2006)

[17] A critical discussion about the homo sociologicus and its explanatory value can be found in Grebing (2008)

[18] An example of a comparision with other models (role sets) can be found in Nixdorf (2007)

[19] A reference towards the individualization and its conflicts can be found in Schlotterbeck (2007)

[20] Compare to Rapoport and Chammah (1965) and Poundstone (1992)

[21] Also compare to Simmel (1890)1890 ??? for additional background information of Georg Simmels psychologicial and sociological experiment of subjective perception.

[22] Compare to Gerhard (1988), who refers to Max Weber, Emile Durkheim and Georg Simmel.

[23] Compare to Flam (1989) with the description of the motivation in the emotional man actor model.

[24] Although the emotional man as an actor model does not purely rely on internal driving factors (like the homo oeconomicus)

[25] Compare to Schimank (2009, p.97)

[26] As an example: A mother is supposed to show an equivalent of love towards both of her children, although she might have stronger feelings for one of them.

[27] ARPA stands for Advanced Research Project Agency, which mainly focuses on topics of defense and military, due to the time of 1958 (where it was founded). The influence of the cold war also was strongly preasuring on digital communincation.

[28] A host is defined as a computer or a router, which allows data traffic with other computers via cable or wireless network connections.

[29] A router describes a technical device to structure the flow of data within the Internet network. The router technology, their performance increase and the usage of new transmitting techniques, such as fiber-glass allowed a significant increase of the data rate. Refer to Moore’s law (Patterson and Hennessy, 2010, p. 28) in this context for the growth in hardware performance.

[30] The most important changes witt?? the technical standards were the communication protocols (TCP/IP, UDP, etc.) to ensure a communication in between the hosts. Based on this data traffic and the increase in network performance, the content of the Internet and its opportunities grew significantly.

[31] The most important languages for the Intenet evoluation were HTML for the design of web-content, Java for the design of applets and based on the evolution of the last years (Web 2.0) several newer context sensitive languages, such as XML, Pearl, PHP, SQL and semantic languages.

[32] Within the increase in potential users, the network technology and the structure of the Internet completely changes. Once the potential of the network was discovered, the investment in modern technology, new server systems and infrastructure were following naturally.

[33] Compare to comScore (2008) and Internetworldstats (2008).

[34] The Web 2.0 evolved roughly over the last five years.

[35] A blog is a type of website or part of a website. Blogs are usually maintained by an individual with regular entries of commentary, descriptions of events, or other material such as graphics or video.

[36] Web 3.0 acts as one of the terms to describe the evolutionary stage in between the network status of the Internet, following the Web 2.0. It also includes interaction forms, which are currently technically or practically not feasible at this time. Compare to Harris (2008).

[37] Compare to figure 3, the size of the field relates to the overall amount of interaction within a given segment compared to the whole Internet.

[38] The decision for online communities against other possible communication forms will be discussed in the research framework section of this thesis.

[39] As a pedagogic student and a game-designer Prensky evaluated the change in behaviour within the Internet and discovered a sharp cut in between the older generation and the young ‘digital natives’.

[40] A detailed argumentation about the sampling is featured in Chapter 3.

[41] Compare to Prof. Buhl targeting the current perception of digital natives: (last checked 25.05.2010).

[42] Compare to (Palfrey and Gasser, 2008, p.2ff.)

[43] Which is based on the rapid cut in between nearly no Internet (in 1990) and a complete digital environment with over 1 billion users (in 2008).

[44] The definition of the Encyclopaedia Britannica and the three definitions from the table.


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Digital Natives Actor Models Homo Oeconomicus Homo Sociologicus Emotional Man Internet Social Communities Online Gaming Online behaviour




Titel: Actor Models and Digital Natives