How someone behaves verbally, physically, or through their presence in a social context influences the behavior of other people in that context. This is a logical and practical assumption about any form of shared human activity. The variety of ways that behavior takes shape and is repeated over time and situations is referred to as “social interaction structure.” The concept of structure also implies that observable patterns of behavior give individual acts, messages, and other behaviors a frame of reference that can be used in their interpretation. The study of social interaction structures also encompasses analyses of natural language in multi-speaker conversations. Scholars who explore language-based approaches to social interaction often focus on how rules of language use and norms governing social behavior influence communication practices (McLaughlin 1984). The study of social interaction structure is also closely aligned with the study of communication as a dynamic process and is often used as the basis for empirically representing communication systems. Social interaction structures are studied in a number of sub-fields including group, intercultural, interpersonal, and organizational communication.
Identifying And Interpreting Social Interaction Structures
Interpreting social interaction structure involves applying theories about how social interaction is, or should be, organized to the results of observations and measurements of social activity. The content of social interaction structures can range from ordinary social behaviors, like words and physical movements, to the inclusion of graphical or melodic representations of ideas, thoughts, and emotions. Researchers may use very literal representations of actual messages (e.g., questions, statistics, etc.) or more generally descriptive terms reflecting broader categories of message themes (e.g., assertive, passive, etc.). Researchers also combine verbal and nonverbal messages together in making inferences about message content (e.g., expressions of sarcasm or irony).
An important variable used in defining the organization of communication processes is time. Time may account for the duration of events observed during social interaction as well as their rate of occurrence (the number of instances a behavior occurs in a given time unit). A related concept is cyclicity. Cycles represent structures based on the repetition of behaviors. Greeting rituals are examples of cycles that are an almost taken-for-granted part of ordinary social interaction. Cycles can also define the intervals between separate occurrences of social interaction. The intensity of emotional involvement displayed by people in a dispute, for example, can be judged by how little time elapses between messages or turns at talk.
Theoretical guidance is used in identifying message content and procedures for determining how messages are linked and interpreted. Social interaction structures can be classified into one or more of four identifiable patterns: distributional, sequential, temporal, and relational (Mabry 1999). These patterns represent increasingly complex explanations of the underlying social interaction.
Distributional structures reveal variability in the frequency or rates of occurrence of social interaction. Classification measures of messages and/or speakers are designed to indicate the extent to which behavior is equally or unevenly distributed according to a method for defining the behavior. The examination of distributional structure is a basic result obtained from analyses of communication content.
Bales’s interaction process analysis (IPA) observation system, for example, classifies message acts uttered in group discussions according to whether they represent questions or attempted answers regarding information, opinion, or suggested action, or are positive or negative social-emotional expressions; overall, 12 types of messages expressed by group members are measured (e.g., agrees, gives suggestions, asks for information, disagrees, etc.). In his research using IPA, Bales found that a typical group problem-solving session produced about five times as many attempted answers as it did questions and roughly twice as many positive acts as negative acts; individual message category distributions showed that giving information accounted for the largest amount of interaction, about 30 percent, compared with positive or negative expressions of friendliness, which each accounted for about 3 percent of group interaction. Distributional structures were quite different in groups where members were satisfied or dissatisfied, experienced protracted conflicts, or worked under intense time pressure (see Bales 1999 for a thorough summary of his research and its implications). Distributional structures are used when communication research goals emphasize the types of messages shared during social interaction.
Sequential structures reflect the event order of messages involved in communication episodes or streams of conversation such as greetings, agreements, disagreements, or attempts at invoking or acceding to power displays. Norms of social interaction lead us to expect that a message exchange where, for example, person A says, “I agree” is likely to stimulate a different set of message responses from person B (or other parties) than if person A said “I disagree”. Sequential structures are also instrumental in revealing how conversations are organized. The fact that speakers take turns helps make conversations predictable. Conversational organization also helps to explain speakers’ intentions and goals as communicators. How certain types of messages precede or follow each other is important for understanding whether speakers are being argumentative, dominating, playful, or sarcastic.
Rogers and Farace’s (1975) transactional method for analyzing relational communication identifies sequential structures based on influence control behaviors. These researchers analyzed records of conversations between relational partners to reveal successive pairs of sequentially occurring interpersonal control messages. Three sequential patterns of influence control structures emerged: symmetrical, complementary, or transitory. Symmetrical structures involved message sequences where both parties enacted the same type of control message. Complementary structure involved message sequences where one person’s message attempted to gain control and the other person was signaling a willingness to yield control. A transitory sequence occurred when a message either attempting to gain or yield control was paired with a message that appeared to neutralize control. Rogers and Farace (1975) also reported that transitory interactions comprised 60 percent of observed exchanges in their sample of couples’ interactions, symmetrical structures were the second most frequent sequence with 28 percent of the exchanges, and complementary exchanges accounted for only 12 percent of the interactions. Such findings suggest that couples spend a substantial amount of time attempting to neutralize their partners’ attempts at relational control instead of either challenging or acceding to the attempted influence. Assessments of sequential structure are often the basis for theories advanced to explain how interpersonal relationships function and why they change.
Temporal structures integrate time-related factors into the organization of social interaction. Temporal structure is also judged by event order cycles based on changes in distributional or sequential structures. For instance, people in meetings may be somewhat more agreeable at the beginning of the meeting and toward the point in time when they want to end the meeting. But agreement may decrease, and disagreements increase, during the middle part of the meeting (Bales 1999). How groups and organizations pursue goals and react to external conditions can be tracked by observing changing patterns of communication that define specific phases or transitional stages.
Temporal structure is also implied in studies of how interpersonal relationships form, evolve, and dissolve. Berger and Calabrese (1975), for example, proposed that initial interaction between strangers passed through three phases motivated by needs for reducing uncertainty. An “entry” phase draws on prior participants’ social information and norms of conduct assumed to be appropriate for that situation. Communication is more structured and oriented toward exchanging descriptive information. A second, “personal” phase may follow the entry phase, when people begin revealing information connected to core beliefs and values and how they perceive the other person(s) in the encounter. An “exit” phase marks the termination of the conversation and the encounter. Messages may revert back to normative expectations about ending social encounters or extend positive impressions made in the personal phase and solicit commitments to future contact. Although a linear trajectory is often implied in studies of temporal structure there is little agreement about the validity of this assumption. There is substantial agreement that studying transitional stages provides important insights about how communication functions in all social contexts.
Relational structures reflect the extent of connectivity between interacting parties (individuals, groups, and/or organizations). They resemble network configurations displaying how communicating units are connected by the amount of messages they exchange or time spent interacting. In romantic relationships, for example, Parks and Adelman (1983) demonstrated that couples were less likely to break up when they increased interaction with their partners and their partners’ network of family and friends. They attributed the results to a decline in uncertainty about the partner caused by increased social information and support generated from becoming more embedded in the romantic partner’s social network.
In his study of organizational networks, Danowski (1980) found network members in production- and innovation-oriented networks had similar beliefs and attitudes that reinforced network affiliations, whereas social maintenance (support) networks drew on more immediate, perceived problem issues. Relational structures are assessed through direct observation of social interaction or by self-reported information obtained from participants. All social contexts contain communication networks; however, people vary greatly regarding how densely connected (embedded) they are in their networks or the strength of their connections, on the basis of how much they interact with others with whom they are connected.
Theories of social interaction structure are often linked to classes or specific types of mathematical analysis (e.g., distributional structure and log-linear models; sequential structure and Markov models). The merging of theory and analysis in the assessment of social interaction structure is often referred to as modeling. Models represent mathematical expressions of how measured variables, like messages, are related to other variables (either messages or other social variables like attitudes or demographic attributes).
Mathematical modeling is uniquely suited to the complexity of analysis required for studying social interaction structures. Models provide relatively straightforward operational maps that can account for the persistence or changeability of a communication structure. The methodological options available for model development also have been demonstrated to provide increasing clarity and validity with more complex structures like sequential, temporal, and relational social interaction structures (VanLear 1996).
- Bales, R. F. (1999). Social interaction systems: Theory and measurement. New Brunswick, NJ: Transaction.
- Berger, C. R., & Calabrese, R. J. (1975). Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication. Human Communication Research, 1(2), 99–112.
- Danowski, J. A. (1980). Group attitude uniformity and connectivity of organizational communication networks for production, innovation, and maintenance content. Human Communication Research, 6(4), 299–308.
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- McLaughlin, M. L. (1984). Conversation: How talk is organized. Beverly Hills, CA: Sage.
- Parks, M. R., & Adelman, M. B. (1983). Communication networks and the development of romantic relationships: An expansion of uncertainty reduction theory. Human Communication Research, 10(1), 55–79.
- Rogers, L. E., & Farace, R. V. (1975). Analysis of relational communication in dyads: New measurement procedures. Human Communication Research, 1(3), 222–239.
- VanLear, C. A. (1996). Communication process approaches and models: Patterns, cycles, and dynamic coordination. In J. H. Watt & C. A. VanLear (eds.), Dynamic patterns in communication processes. Thousand Oaks, CA: Sage, pp. 35–69.