Conversation Analysis

What Is Conversation Analysis?

Conversation Analysis (CA) focuses on how language is used in interaction, rather than simply what is being said. CA researchers recognize that conversation is orderly and that this orderliness can be observed and analyzed.

One of the goals of CA is to describe the procedures that people use to produce and understand conversation.

CA aims to understand how people use language to communicate and relies heavily on the analysis of naturally occurring conversations.

It moves beyond simply interpreting words to consider nonverbal cues, turn-taking patterns, and how participants’ actions shape and are shaped by their social roles.

Through detailed examination of real-world conversations, conversation analysis illuminates how individuals use language to construct meaning, exercise power, and navigate the intricacies of social interactions in various settings.

Who introduced conversation analysis?

Conversation analysis was developed by sociologist Harvey Sacks and his close associates Emanuel Schegloff and Gail Jefferson at the University of California, Los Angeles (UCLA) in the 1960s and early 1970s.

Sacks, Schegloff, and Jefferson laid the groundwork for conversation analysis through their pioneering work on the structure and organization of everyday talk.

They studied recordings of naturally occurring conversations, focusing on the sequential organization of talk, turn-taking, repair mechanisms, and the social actions performed through talk.

Some of their seminal works include:

1. Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696-735.
2. Schegloff, E. A., Jefferson, G., & Sacks, H. (1977). The preference for self-correction in the organization of repair in conversation. Language, 53(2), 361-382.

These studies, among others, established conversation analysis as a distinct field within the social sciences, providing a method for analyzing the intricate details of social interaction through talk.

When to use conversation analysis

Conversation Analysis (CA) helps researchers understand the meanings of real language and how people speak in natural settings, going beyond just the words themselves. CA is particularly useful in analyzing:

• Social interaction: CA examines how people use spoken language to interact, focusing on aspects like turn-taking, interruptions, pauses, intonation, and word stress.
  • This analysis helps reveal the procedures and structures underlying everyday conversations.
• Power Dynamics: The ability to control who speaks, and when, can reveal power dynamics in conversations.
  • For instance, in a courtroom setting, the attorney controls the conversation by asking sequences of questions the witness is expected to answer.
• Institutional Talk: CA observes how participants use talk to navigate formal institutional settings, such as courts or interviews.
  • These settings have defined roles, and the structure of turns is often pre-determined. In less formal institutional settings, such as medical or business environments, participants have more flexibility in their roles.
  • However, conversation analysis reveals asymmetries in these interactions. For example, in doctor-patient interactions, while the conversation might appear conversational at times, the physician typically controls the topics and determines the outcome of the discussion.

Researchers often choose CA because it relies on naturally occurring data, such as recordings of conversations. CA considers the context of the conversation crucial for understanding the meaning of what is said.

CA vs discourse analysis

CA is distinct from discourse analysis (DA). While both explore language in use, they have different focuses:

• Discourse analysis examines a broader range of language use, considering the meaning of words, intentions, and underlying assumptions within a wider social and cultural context.
• Conversation Analysis zooms in on the non-verbal aspects of speech, such as pauses, intonation, and emphasis, to uncover the subtle ways meaning is created in interactions.

The choice between using CA or DA, or employing them together, depends on the research question.

For example, a researcher might use CA to study how doctors and patients negotiate treatment decisions or how lawyers use language to influence a jury.

Sequential organization of talk

Sequencing refers to the way in which turns and actions in a conversation are ordered and related to each other. Let’s look at how each of these elements relates to sequencing:

1. Turn-taking: This refers to the way speakers alternate in taking turns in a conversation. The sequence of turns is a fundamental aspect of the organization of conversation.
2. Adjacency pairs: These are pairs of utterances that are often found together, such as question-answer, greeting-greeting, or offer-acceptance/refusal. The first part of the pair creates a expectation for the second part, thus forming a sequence.
3. Repair mechanisms: These are strategies used by speakers to address problems in speaking, hearing, or understanding. Repair sequences involve the initiation of repair and its completion, forming a sequence within the conversation.
4. Non-verbal cues: These include elements like gaze, gestures, and body posture, which can play a role in the sequential organization of conversation, such as signaling the end of a turn or the beginning of a new sequence.

All these elements contribute to the sequential structure of conversation, which is a key focus of conversation analysis.

By studying how these elements are ordered and related to each other, conversation analysts aim to uncover the underlying structure and organization of talk-in-interaction.

1. Turn-Taking

People in conversations generally respond to each other in a structured process known as turn-taking.

Turn-taking is like sharing in a conversation so everyone gets a chance to speak. It makes sure conversations are orderly, with only one person talking at a time. Turn-taking lets people decide when to start and stop talking, making sure conversations are smooth and make sense.

This system ensures that conversations flow smoothly, with minimal overlapping or awkward silences

The foundational principle of turn-taking is that conversation unfolds one speaker at a time. While this may seem obvious, CA provides a detailed framework for understanding how this is accomplished in practice.

1. Transition relevance places

Transition relevance places (TRPs) are points in conversation where speaker change becomes a possibility. These are often marked by the completion of a grammatical unit, a change in intonation, or a non-verbal cue.

At a TRP, the current speaker can either continue speaking or offer the floor to another participant.

If the current speaker chooses to allocate the turn, they can do so by directly addressing a specific participant or by using a more open-ended cue that allows anyone to self-select.

If the speaker doesn’t select the next speaker, other participants can self-select by starting to speak.

2. Turn allocation

Turn allocation techniques refer to the methods used by participants in a conversation to determine who speaks next.

These techniques are central to the organization of turn-taking, ensuring the smooth exchange of speaking turns with minimal overlapping or interruptions.

There are two primary types of turn allocation techniques: current speaker selects next and self-selection

2.1 Current speaker selects next

This technique involves the current speaker explicitly or implicitly choosing the next speaker.

Addressing a Question: One common method is directing a question to a specific participant, thereby selecting them to provide the answer.

For example, “Ben, do you want some?” explicitly selects Ben as the next speaker.

Affiliation with First Pair-Part: A broader category of utterances, termed “first pair-parts” in conversation analysis, also function as current speaker selects next techniques.

These include greetings, invitations, complaints, and other utterances that initiate specific types of adjacency pairs, creating an expectation for a particular type of response from a selected recipient.

For instance, in the sequence “Hey yuh took my chair by the way an’ I don’t think that was very nice,” the first utterance (a complaint) sets up an expectation for a denial or account from the recipient in the next turn.

Lexical Selection: The current speaker can also use specific words or phrases to indicate who should speak next, such as “never” or “ever” in a series of questions.

It’s important to note that addressing a party doesn’t automatically guarantee they will be the next speaker.

For instance, if B answers A’s question and addresses their response to A, this doesn’t necessarily mean A is selected to speak next.

The context and subsequent actions of the participants will determine the actual turn allocation.

2.2 Self-selection

In contrast to the current speaker selecting the next speaker, self-selection occurs when a participant who was not selected initiates their turn at a transition relevance place (TRP).

• First Starter: The most prevalent form of self-selection is when a participant starts speaking first at a TRP. This is often marked by a slight gap or overlap with the previous speaker.

• Interruption: While less common, self-selection can also occur when a participant starts speaking before the current speaker has reached a TRP, effectively interrupting the ongoing turn.

The turn-taking system prioritizes the current speaker’s right to select the next speaker. If the current speaker doesn’t utilize this option, then other participants can self-select.

This ordering of techniques ensures that conversations maintain their sequential organization and avoid multiple speakers talking simultaneously.

3. Context-dependent nature of turn-taking 

A turn-taking system is considered “context-free” at its foundational level. This means the basic machinery for distributing turns operates consistently across diverse contexts, irrespective of who is speaking, what they are talking about, or their relationship.

This fundamental structure is what allows conversations to happen at all, ensuring that people mostly speak one at a time and transitions are generally smooth.

Context-Sensitivity: Turn allocation techniques aren’t arbitrary; they are influenced by the context of the conversation, the relationship between participants, and the social norms at play.

Understanding these techniques is crucial for researchers to analyze how conversations unfold, how participants manage their turns, and how meaning is co-constructed in interaction.

This context-free system becomes “context-sensitive” in its implementation. This means that while the underlying rules remain constant, how those rules are actually used to allocate turns can vary greatly depending on:

• Number of Participants: With more participants, the dynamics of turn distribution become more intricate, requiring adjustments to strategies for getting, keeping, or even relinquishing turns.
• Relationship Dynamics: The relationship between speakers (e.g., friends versus strangers, superiors versus subordinates) profoundly shapes turn-taking. Factors like relative status, familiarity, and existing power dynamics can influence who initiates, interrupts, or holds the floor for longer.
• Social Norms: Societal and cultural conventions heavily influence turn-taking. Norms dictate acceptable pauses, interruption etiquette, and how speakers signal turn transitions. These norms, often implicit, contribute to the “orderliness” of conversation within specific cultures or communities.
• Purpose of Conversation: The goal of a conversation (e.g., casual chat, formal debate, institutional interaction) influences turn-taking. For example, debates have pre-allocated turns, unlike informal conversations where turn allocation is more fluid.

• Turn Content as a Factor: Importantly, while the turn-taking system is indifferent to the content of turns, this doesn’t mean content is irrelevant. What speakers say in their turns provides the context for subsequent turns. For example, a question (content) projects an answer as the relevant next action, shaping turn allocation.

In essence, while the underlying system provides the framework, the actual dance of conversation, with its nuances and adjustments, emerges from the interplay of this context-free base with the ever-changing dynamics of context, relationships, and social expectations.

2. Adjacency Pairs

Adjacency pairs are pairs of turns in conversation that are closely related to each other.

Adjacency pairs are inherently sequential, with the first part of the pair making the second part conditionally relevant

The fundamental unit of sequencing is the adjacency pair, consisting of two utterances by different speakers. The first part sets an expectation for a specific type of response in the second part. Examples include question-answer, invitation-acceptance/decline, and greeting-greeting

For example, a greeting is typically followed by another greeting, a farewell by a farewell, and a question by an answer. These pairs are considered the basic building blocks of conversational sequences.

Here are some key features of adjacency pairs:

• They consist of two turns made by different speakers.
• These turns are typically adjacent to each other, meaning there is no intervening talk between them.
• The turns are ordered so that the first pair part (FPP) always comes before the second pair part (SPP). For example, a question always precedes its answer.
• The turns are differentiated into pair types where the FPP makes a particular type of SPP relevant. Examples of adjacency pair types include:
  • question – answer
  • greeting – greeting
  • summons – answer
  • telling – accept

The concept of conditional relevance is central to understanding adjacency pairs. This principle states that the first part of an adjacency pair establishes an expectation for a particular type of second part.

If the expected second part does not occur, it is considered “noticeably absent.” This absence becomes significant for analyzing the conversation.

Adjacency pairs can be expanded in several ways:

• Preface: A preface expands an adjacency pair with pre-expansions (like disclaimers), which are sequences that prepare for upcoming talk and project that further talk will follow.
• Extension: An extension expands an adjacency pair with post-expansions (like assessments), which are sequences that follow and extend the base adjacency pair.
• Insertion: Insert expansions, which are nested between the first and second pair parts of an adjacency pair, may be used to clarify information before responding to the first pair part

It is important to note that while adjacency pairs are a fundamental aspect of conversation analysis, they are not the only way conversations are organized.

3. Repair Mechanisms

Repair in conversation analysis refers to the processes by which speakers address problems that arise in talk. These problems can be related to hearing, production, or understanding.

Rather than being a negative phenomenon, repair is a natural and essential self-regulating device crucial for maintaining coherence in conversation.

Types of repair

Repair mechanisms can be categorized based on who initiates the repair (the speaker or the recipient of the problematic utterance) and who carries out the repair. This results in four primary types of repair:

1. Self-initiated self-repair: The speaker of the problematic utterance both identifies and resolves the issue.
2. Self-initiated other-repair: The speaker identifies a problem, but the recipient provides the solution.
3. Other-initiated self-repair: The recipient of the problematic utterance points out the issue, and the original speaker resolves it.
4. Other-initiated other-repair: The recipient both identifies and resolves the problem in the speaker’s utterance.

Preference for self-repair

While both speakers and recipients can initiate repair, there’s a general preference for self-initiated repair over other-initiated repair.

This suggests that the conversational system prioritizes speakers taking responsibility for their own utterances.

Other-initiated repair often takes the form of signaling a problem, prompting the original speaker to carry out the repair (other-initiated self-repair).

This highlights that even when others initiate repair, the system is often structured to ultimately facilitate self-repair.

Repair positions and turn-taking

Repair is also closely tied to turn-taking systems in conversation. The timing of repair initiation, relative to the problematic utterance, shapes how repair unfolds:

• Same-turn repair: The speaker initiates repair within the same turn as the problematic utterance, often using non-lexical cues like cut-offs, sound stretches, or pauses.
• Transition space repair: Repair happens in the brief silence between turns, after the problematic turn.
• Second position repair: Repair occurs in the turn immediately following the one containing the problem. This often involves the recipient initiating the repair.
• Third position repair: Repair takes place in the third turn after the problematic utterance.
• Fourth position repair: While less common, repair can occur in the fourth turn, usually involving the recipient addressing a persistent issue.

The sequential organization of repair, with opportunities for self-repair preceding those for other-repair, further emphasizes the system’s design favoring self-correction.

Repair in online communication

Repair in online communication, while sharing similarities with face-to-face interaction, also exhibits differences due to the nature of the medium.

One notable difference is the absence of same-turn repair in online interactions, as any corrections made during typing wouldn’t be visible to others.

Additionally, online communication might see a weakening of the preference for self-repair, as the recipient might resolve the issue more efficiently in some cases.

4. Non-Verbal Cues In Communication

Non-verbal cues are central to human communication, and though communication is possible without them (as in telephone calls), that does not make them peripheral to the process.

Human communication is inherently multimodal, meaning it uses all available modes to convey information between speakers and recipients. These can include less easily recorded modes like smell or taste.

How non-verbal cues shape meaning

Non-verbal elements like laughter, smiling, intonation, and stress act as contextualization cues. They work alongside language to shape how words are understood in a given interaction.

This means that while they don’t inherently encode meaning on their own, they influence how spoken words are interpreted.

For example, a statement can be interpreted literally if accompanied by laughter or a smile, while intonation and stress can convey sarcasm or a negative response.

Gaze in conversation

Gaze, as an act of seeing and a communicative act, plays a significant role in social interaction. It signals what a participant is attending to and can be used to solicit a response, even without explicit verbal prompting.

For instance, if a speaker has not received a response to their talk, they might use gaze to elicit one, which could be verbal or take the form of a gesture.

Gesture as Communication

Gestures, which convey meaning through bodily action, are not incidental but a core part of interaction. They have a central communicative function that contributes to the overall meaning-making in conversation. Some of the roles gestures play within interactions include:

• Turn Allocation: Gestures can be used to gain the floor in a conversation, acting as a way to signal a desire to speak.
• Turn-Taking Organization: They contribute to the non-verbal aspects of turn-taking, such as providing cues for turn completion.
• Replacing Linguistic Forms: Gestures can stand alone as complete turns, replacing verbal communication entirely. For instance, nodding or shaking one’s head can convey agreement or disagreement, a wave acts as a greeting or farewell, and redirecting gaze can be a response to being addressed.

Integrating gesture, gaze, and talk

In conversation, gestures, gaze, and talk work in a coordinated way to construct meaning. Gestures can be used to introduce non-present entities into a conversation, functioning similarly to how pointing incorporates physically present objects.

For example, a speaker might use a gesture to indicate a specific location on a screen while simultaneously using the word “problem.” In this case, both the gesture and the spoken word are deictic—they work together to direct attention to a particular spatial location and establish shared focus.

However, the gesture is not merely a repetition of the spoken word. The spoken word, in this instance, relies on the gesture to achieve its full meaning; without it, the spatial location might remain unclear.

This integration of gesture and talk creates a laminated action, where both modes are essential for conveying the intended meaning.

Non-verbal cues in conversation analysis

Conversation analysis (CA) emphasizes the significance of non-verbal cues in understanding social interaction.

Analyzing elements like speaking speed and intonation provides valuable context for comprehending the nuances of social interaction.

For instance, a speaker’s confidence level when answering a question can be inferred from their intonation and pauses.

Hesitations or pauses might suggest uncertainty as the speaker searches for the right words. Conversely, emphasizing certain words can convey authority and expertise.

By considering these non-verbal cues, CA provides a richer understanding of the meaning conveyed in interactions beyond the literal words spoken.

Steps for Conducting CA

1. Data Collection: Collect data using audio or video recordings of naturally occurring interactions.
2. Transcription: Transcribe the recordings in detail, using a system like the Jeffersonian transcription system to capture pauses, intonation, and other non-verbal cues.
3. Unmotivated Looking: Listen to the recordings multiple times without any pre-existing theories in mind.
4. Identify Phenomena: Identify recurring patterns in the data, such as turn-taking, repair strategies, and the use of specific words or phrases.
5. Analyze the Data: Analyze the identified phenomena. For instance, how do speakers use pauses to manage turn-taking or how do they repair misunderstandings?
6. Develop an Analysis: Develop a clear and concise analysis, focusing on the sequential organization of the talk. For example, how does a speaker’s turn relate to the previous turn?
7. Contextualize the Analysis: Consider the context of the interaction. What are the social and cultural norms that might be influencing the interaction? What are the individual differences between the speakers?

Step 1: Data Collection

Data Collection in CA focuses on gathering recordings of these naturally occurring conversations. This could be conversations between friends, family members, or even strangers. The idea is to capture how people actually talk, not how we think they talk.

The goal is to gather data that accurately reflects real-world conversations for analysis.

Example

For example, a researcher studying how people apologize might collect recordings of conversations where apologies occur naturally, such as between friends who had a disagreement. They wouldn’t ask friends to stage an argument and apologize, as this wouldn’t reflect how people genuinely interact.

The researcher might start by identifying situations where apologies are likely to occur, such as after a friend forgets a promise or accidentally says something hurtful.

They could ask their friends if they would be willing to be recorded having conversations in these types of situations.

The goal is to capture authentic apologies in their natural context, providing insights into how people use language to repair relationships and navigate social dynamics.

It is important to record data in a way that captures as much detail as possible, including pauses, intonation, and word stress. This can be achieved by using audio or video recording equipment.

The Observer’s Paradox

Conversation Analysis (CA) researchers acknowledge that recording interactions for analysis might influence how naturally participants behave.

This is called the “observer’s paradox”: when people know they’re being watched, they may not act like they normally do. Ideally, CA seeks to understand how people interact when they are not being observed.

Researchers try to minimize the impact of recording by using unobtrusive methods. For example, they might have an “absent observer,” where only a recording device is present, not the researcher themselves.

However, even when participants aren’t aware of a recording device, the possibility of their behavior being influenced by the research process remains.

Participants’ Awareness of Recording

There is some evidence suggesting that recording devices might not always significantly affect interaction. Speer and Hutchy (2003) argue that participants’ reactions to being recorded can be analyzed within the context of the interaction itself. The impact of recording is complex and varies depending on the specific participants and the situation.

Importantly, ethical considerations in CA research require that participants are always aware they are being recorded and consent to it. While this awareness might impact the naturalness of their interaction, ethical research practices prioritize informed consent.

Step 2: Transcription

Transcribing talk in conversation analysis involves more than simply recording the words spoken. Conversation analysts need to know “how it was said” in addition to “what has been said”. The transcript should capture features like pauses, intonation, stress, and overlapping speech.

Conversation analysis employs a meticulous transcription system developed by Gail Jefferson. This system is designed to capture the nuances of naturally occurring talk for in-depth analysis.

Here are key aspects of this transcription technique:

1. Detailed Representation: This transcription method goes beyond just words, aiming to represent pauses, overlaps, intonation, and even non-verbal aspects like laughter and breathing. This intricate approach allows researchers to see the transient, complex nature of talk in a static, analyzable format.
2. Specialized Symbols: The Jeffersonian transcription system utilizes a unique set of symbols to denote these conversational elements, like micropauses, overlapping speech, intonation, and more. This system helps researchers capture the precise delivery of talk, including pace, overlapping talk, and intonation.
3. Iterative Refinement: Creating a conversation analysis transcript is an iterative process. Researchers often start with basic elements like words and pauses, then layer in more complex information like intonation, stress, and overlapping speech. This layered approach to transcription ensures the capture of subtle details for a comprehensive analysis.
4. Importance of Context: Transcripts alone are not sufficient for analysis; they are always used alongside recordings. Researchers constantly revisit and refine their transcripts based on repeated listening to the recordings. Capturing non-verbal cues like gaze, gestures, and object interaction requires video recordings, adding further complexity to the transcription process.

Conversation analysis emphasizes recording interactions in natural settings using audio and video technology. Despite limitations in capturing every detail, recordings offer significant advantages over relying on intuition or invented sentences.

Transcribing these recordings is a selective process, influenced by the researcher’s analytical goals. This meticulous approach allows researchers to identify recurring patterns and subtle nuances in social interactions.

Software applications that automatically generate transcripts from spoken language data offer limited use in conversation analysis.

While useful for basic transcription, these applications struggle with overlapping talk and lack the capacity to capture the detailed nuances crucial for in-depth analysis.

Specialized Symbols

The Jefferson Transcription System meticulously details the nuances of spoken interaction, going beyond mere words to include pauses, overlaps, intonation, and even non-verbal elements like laughter.

This system is not simply about accurate documentation; it provides a structured framework for analyzing the complexities of naturally occurring talk.

Turn-taking

Turn-taking is the systematic allocation of opportunities to talk, and the regulation of the size of those opportunities.

To account for turn-taking dynamics, transcripts aim to capture the details of how turns are taken in talk-in-interaction.

These details include the precise points at which turns begin and end, including overlaps, gaps, pauses, and audible breathing.

• Overlapping Speech: Square brackets ([]) precisely mark the points where simultaneous speech occurs, capturing the intricacies of interruptions, simultaneous starts, and turn-taking competition.
• Contiguous Utterances: An equal sign (=) signifies a swift transition between consecutive utterances without a discernible pause, highlighting the rapid flow of speech.
• Breathing: The symbol “.hhh” indicates an in-breath, further adding to the transcription’s representation of the speaker’s delivery.
• Pauses: The duration of silences is precisely measured, typically in tenths of a second, using numerals within parentheses. This precision highlights the interactional significance even brief pauses can hold, as demonstrated by research showing the impact of pauses as short as two or three-tenths of a second.

Speech Delivery

To account for the characteristics of speech delivery, transcripts mark noticeable features of stress, enunciation, intonation, and pitch.

For example, if a speaker noticeably extends a word, colons are inserted into the word at the point of extension. The longer the audible extension, the more colons are inserted.

• Intonation: Punctuation marks are repurposed to denote intonation: a period (.) for a falling tone, a question mark (?) for a rising tone, and a comma (,) for a non-final, flat tone.
• Stress: Underlining beneath a word signifies emphasis or stress, drawing attention to words given prominence in spoken delivery.
• Sound Stretching: Colons (:) visually represent the lengthening of a sound. The number of colons corresponds to the duration of the extension, providing a visual representation of drawn-out pronunciation.
• Inaudible Speech: Parentheses with empty space ( ( ) ) are used to denote instances where speech is indistinguishable, acknowledging the limits of transcription while maintaining the sequential flow of the conversation.

Beyond Words: Capturing Non-Verbal Communication

While the Jefferson Transcription System excels in capturing the nuances of spoken language, it also acknowledges the importance of non-verbal elements in interaction.

Researchers have expanded the system to encompass visual information, especially in video-recorded data.

For example, symbols like paired asterisks (*) or carets (^) can denote gestures made by different speakers.

Descriptive annotations within double parentheses ( (()) ) provide context about actions, like a car turning a corner, enriching the understanding of the interaction’s setting and potential influence on the dialogue.

Step 3: Unmotivated Looking

Listen to the recordings multiple times without any pre-existing theories in mind.

Listening to the recordings

During the “Unmotivated Looking” stage of conversation analysis (CA), the researcher repeatedly listens to the same recordings.

This process aims to understand what transpires in the data without imposing preconceived theories or expectations.

The focus is on uncovering naturally occurring patterns and structures within the conversation.

Openness to discovery

Unmotivated looking encourages the analyst to be receptive to discovering unexpected phenomena in the data.

Rather than searching for specific pre-identified elements, the researcher maintains an open mind, allowing the data to guide their observations.

This approach helps in identifying subtle but significant aspects of social interaction that might otherwise be overlooked.

Noticing and identifying actions

The process involves carefully attending to the details of the talk, including seemingly insignificant features. The goal is to understand the actions being performed through language.

For example, a researcher might notice a particular phrase and try to identify its effect on the subsequent conversation.

This can involve identifying how participants use specific practices to achieve communicative goals, like making a request or offering an assessment.

Challenges and considerations

While seemingly straightforward, unmotivated looking presents challenges. Researchers acknowledge that achieving complete neutrality is difficult, as prior knowledge and research interests inevitably shape perception.

The process involves balancing openness to new discoveries with the existing body of knowledge in CA.

Despite these challenges, unmotivated looking remains a fundamental principle in CA, providing a foundation for identifying and understanding the intricate ways people communicate and interact.

Step 4: Identify Phenomena

The focus shifts to identifying recurring patterns in the data, such as turn-taking, repair strategies, and the use of specific words or phrases.

These patterns can manifest in various ways, including:

• Turn-Taking: This involves analyzing how speakers alternate turns in a conversation, examining elements like turn allocation and speaker selection. For instance, identifying instances where the current speaker selects the next speaker or examining how overlapping talk is managed.
• Repair Strategies: This entails studying how participants address and resolve communication breakdowns or misunderstandings. Examples include noting where repair work occurs, identifying the type of repair (e.g., self-initiated self-repair), and analyzing how participants construct and respond to repair attempts.
• Use of Specific Words or Phrases: This involves recognizing recurring linguistic features, such as particular words, phrases, or grammatical structures that hold significance in the data. This can include examining the use of explicit repair devices (e.g., “Excuse me”) or identifying specific formats used to perform particular actions (e.g., “You should X” for requests).

The goal is to move beyond individual instances and identify patterns that reveal how participants understand and navigate social interaction.

For example, analyzing instances of third-position repair, a pattern where a speaker clarifies their prior utterance after the recipient’s turn shows a problem in understanding.

Recognizing these recurring patterns helps researchers develop a deeper understanding of the practices and conventions governing conversation.

Step 5: Analyze the Data

The next step in analyzing conversational data is to examine each case in the collection by analyzing : activity, participation, position, composition, and action of the conversation.

Analyzing each of these aspects creates an understanding of how the interaction functions line by line.

• Activity: This refers to what participants are doing together through their interaction. When examining activity, some questions to consider are:
  • What are the circumstances of the interaction?
  • Do the participants share a common goal, environment, or communication medium?
  • Is there a goal, or is it more loosely organized?
  • Are certain actions done at certain times, in a certain order, or by certain participants?
• Participation: This refers to the roles participants occupy throughout the interaction. When examining participation, some questions to consider are:
  • What roles do the participants occupy generally (e.g., speaker vs. the person who just finished speaking).
  • What roles do participants occupy turn-by-turn (e.g., speaker and recipient)?
  • What roles do participants occupy within a sequence (e.g., someone initiating a repair)?
  • What roles do participants occupy within the specific occasion (e.g., caller and receiver)?
  • How do the participants navigate and change roles?
• Position: A characterization of action should come after an adequate analysis of sequence structure and turn construction.
• Composition: A characterization of action should come after an adequate analysis of sequence structure and turn construction.
• Action: This refers to what the talk and conduct accomplish in the interaction. The location of the conduct within the conversation and how it is formatted make up the action.

The goal of analyzing each case in the collection line by line is to be able to produce a comprehensive analysis of each conversation.

As you examine the conversations, take notes and modify the formal description of the phenomenon as needed.

Step 6: Develop an Analysis

The final step in analyzing conversational data is to develop a formal account of the phenomenon.

The criteria used to identify the phenomenon and its boundaries are key to this account, along with an analysis of variations across the entire collection of conversations.

The account should describe the phenomenon’s structure, including the linguistic forms and social actions involved. It should explain how it functions, the conditions in which variations arise, and the interactional problem it addresses.

Example of developing an analysis

The analysis of a specific conversational phenomenon, such as a particular type of question-response sequence, could involve examining how the use of specific linguistic forms, such as hedges, relates to the participants’ understanding of each other’s knowledge about the topic being discussed.

For instance, the use of the word “sounds” in the assessment “That sounds interesting” may indicate that the speaker assumes the recipient has limited knowledge of the assessable object.

A formal account of this phenomenon might propose that speakers use hedges like “sounds” to convey a lack of certainty about the assessment, which is appropriate when they believe the recipient has no direct experience with the object being assessed.

This account would need to be grounded in evidence from the collection of conversational data, showing that speakers consistently use hedges in these specific contexts.

The account might further explain that the use of hedges in assessments serves to manage social epistemics by acknowledging the recipient’s limited knowledge and avoiding potential challenges or disagreements.

This explanation would connect the observed linguistic behavior to a broader social function, demonstrating how the phenomenon contributes to the smooth flow of conversation.

Step 7: Contextualize the Analysis

Consider the context of the interaction.

When analyzing conversations, it is important to consider the social and cultural norms that might be influencing the interaction.

For example, the way people take turns speaking or the types of speech acts that are considered appropriate can vary depending on the culture.

Additionally, the social relationships between the speakers, such as whether they are friends, family members, or strangers, can also influence how they interact.

It is important to note that conversation analysis (CA) focuses on analyzing how participants in an interaction understand and shape the interaction, rather than imposing external assumptions about the influence of social categories or relationships.

Next-turn proof procedure

Next-turn proof procedure is a method in conversation analysis (CA) where a turn is analyzed as evidence of its speaker’s understanding of the prior turn. This method is a basic tool in CA because it illustrates how the structure of talk is oriented to the performance of speaking.

The next-turn proof procedure is based on the fact that the turn-taking system requires speakers to display their understanding of the prior turn in order to produce a relevant next turn.

For example, when a speaker produces a question, the next speaker is expected to produce an answer. By producing an answer, the next speaker displays their understanding that the prior turn was a question. This understanding is what is analyzed in next-turn proof procedure.

Next-turn proof procedure is a valuable tool for analysts because it allows them to understand how participants are making sense of each other’s turns.

This method ensures that the analysis is grounded in the participants’ own understanding of the interaction, rather than the analyst’s assumptions.

Here are some questions to consider when contextualizing conversational analysis:

• What are the cultural backgrounds of the speakers?
• What is the relationship between the speakers? (e.g., friends, family, colleagues, strangers)
• What is the setting of the interaction? (e.g., formal or informal, public or private)
• What is the purpose of the interaction? (e.g., to exchange information, to build relationships, to accomplish a task)

By considering these contextual factors, researchers can gain a more complete understanding of the interaction and how the participants are using language to achieve their goals.

Tips for Conducting Conversation Analysis

1. Focus on naturally occurring interactions: Use actual talk in context, such as recordings from everyday conversations or institutional settings. Conversation Analysis (CA) emphasizes studying real-world language to understand how communication works in its natural environment. Avoid using manipulated or artificial data.
2. Prioritize detailed transcription: Capture the nuances of spoken interaction, including pauses, intonation, word stress, and non-verbal cues. Transcribe repetitions, grammatical errors, and other speech features that might be relevant for understanding the interaction. The Jeffersonian transcription system is commonly used in CA research to denote these details.
3. Use video recording for comprehensive data: Video recordings capture non-verbal cues like gestures, body language, and shared visual context that might be missed in audio-only recordings. While audio recording has its advantages (e.g., less intrusive, easier to transcribe), video provides a more complete record of the interaction for analysis.
4. Engage in ‘unmotivated looking’: Listen to the recordings repeatedly without preconceived notions to identify interesting or puzzling patterns. This inductive approach helps uncover recurring patterns and discover new insights directly from the data.
5. Analyze sequential organization: Examine how turns are taken, actions are coordinated, and meaning is co-constructed within the conversation flow. The order and placement of utterances are crucial for understanding their meaning and function.
6. Consider the context: Acknowledge the influence of social and cultural factors, individual differences, and the specific situation on the interaction. CA recognizes that communication is shaped by its context and avoids assuming universal rules of interaction.
7. Avoid imposing pre-theorized frameworks: Let the data guide the analysis and develop theoretical insights inductively. While CA research might incorporate existing theories, the primary focus is to understand interactional patterns based on evidence from the data itself.
8. Use clear and consistent notation: When presenting findings, employ a widely recognized transcription system and explain any deviations or specific notations. Consistent notation ensures that others can understand and interpret the analysis.
9. Thoroughly explain the data and analysis: Present findings in a way that allows the audience to understand the context, the reasoning behind the analysis, and the significance of the observed patterns. Provide sufficient detail to support the claims and enable others to follow the analytical process.

Further Information

Maynard, D. W., & Heritage, J. (2005). Conversation analysis, doctor–patient interaction and medical communication. Medical Education, 39(4), 428–435.

Peräkylä, A., Antaki, C., Vehviläinen, S., & Leudar, I. (Eds.). (2008). Conversation analysis and psychotherapy. Cambridge University Press.

Sacks, H., Schegloff, E. A., & Jefferson, G. (1978). A simplest systematics for the organization of turn taking for conversation. In Studies in the organization of conversational interaction (pp. 7-55). Academic Press.

Schegloff, E. A. (1987). Analyzing single episodes of interaction: An exercise in conversation analysis. Social psychology quarterly, 101-114.

Schegloff, E. A. (1992). Repair after next turn: The last structurally provided defense of intersubjectivity in conversation. American journal of sociology, 97(5), 1295-1345.

Schegloff, E. A. (1993). Reflections on quantification in the study of conversation. Research on Language and Social Interaction, 26(1), 99–128.

Schegloff, E. A. (2002). 18 Beginnings in the telephone. Perpetual contact: Mobile communication, private talk, public performance, 284.

Schegloff, E. A. (2007). Categories in action: Personreference and membership categorization. Discourse
Studies, 9(4), 433–461.

Schegloff, E. A. (2007). Sequence organization in interaction: A primer in conversation analysis I (Vol. 1). Cambridge university press.

Schegloff, E. A. (2007). A tutorial on membership categorization. Journal of pragmatics, 39(3), 462-482.

Schegloff, E. A., & Sacks, H. (1973). Opening up closings.

Speer, S. A., & Hutchby, I. (2003). From ethics to analytics: Aspects of participants’ orientations to the presence and relevance of recording devices. Sociology, 37(2), 315-337.

Stivers, T. (2007). Prescribing under pressure: Parent-physician conversations and antibiotics. Oxford University Press.