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Communication Research

by: Jamar Davis

Communication Research COMM 2030

Jamar Davis
GPA 3.9

Tami Tomasello

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Tami Tomasello
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This 18 page Study Guide was uploaded by Jamar Davis on Sunday October 11, 2015. The Study Guide belongs to COMM 2030 at East Carolina University taught by Tami Tomasello in Fall. Since its upload, it has received 25 views. For similar materials see /class/221344/comm-2030-east-carolina-university in Communication at East Carolina University.


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Date Created: 10/11/15
Communication Research CHAPTER l4 Review Chapter 1 Introduction to Communication Research Research the discovery of answers to questions through the application of scienti c and systematic procedures Social Science Research Conducted through the use of scienti c and systematic mathods and it is based on the assumption that research can uncover patterns in the lives of people Empirical both methods are based on observations or experiences of communication Propietrary Research research that is commissioned by an individual or organization for its own use Goals of Research MDescribing behavior entails describing outcomes processes or ways in which variables another name for the concepts we study are related to one another Determining the cause or causes of behavior is of interest to communication scholars because knowing the cause of something allows scholars to later plan interventions or develop training to increase the effectiveness of communication MPrealicting behavior If behaviors are predictable then we can anticipate what will happen in the future Going beyond describing determining causes and predicting explaining behavior means understanding why a behavior occurs Theory a related set of ideas that explain how or why something happens Quantitative Methods Generally speaking research that relies on numerical measurement Qualitative Methods Generally speaking research in which the researcher is the primary observer or data collector Hypothesis a tenative educated guess or proposition about the relationship between two or more variables Research Question Asks what the tentative relationship among variables might be or asks about the state or nature of some communication phenonmenon The Nature of the Questions 4 types of questions Questions of Fact Provides de nitions for phenomena in which we are interested Whereas you may believe that all de nitional issues have been addressed Remember that new communication situations and environments and changing societal values create new areas to explore and de ne Questions of Variable Relations examine if how and the degree to which phenomena are related Questions of Value Ask for indinuals subjective evaluations of issues and phenomena Questions of Policy Communication researchers seldom test policy issues directly but the results of research studies are o en used to recommend a course of action Summary Research is asking questions and finding answers Scholarly research is the discovery of answers to questions through the application of scientific and systematic procedures Academic research follows accepted norms and procedures that have been adopted by scholars from many disciplines In the process of scientific discovery and explanation four outcomes are sought describing behavior determining causes of behavior predicting behavior and explaining behavior The best research is that which is driven by theory validates a theory further explains a theory challenges an existing theory or aids in the creation of theory As a social science communication researchers use both quantitative and qualitative methods The study of communcation from a social science perspective looks for patterns across cases and focuses on symbols used to construct messages messages the e quotects of messages and their meanings Communication scholars start with an interesting question and then formulate a formal research question or hypothesis Questions suitable for communication research are those for which the researcher has a personal interest one that is of social importance and one that has or can help develop theoretical significance A hypthesis is a tenative educated guess or proposition about the relationship between two or more variables A formal research question asks what the tentative relationship among variables might be or asks about the state or nature of some communication phenomenon Research is judged to be scientific by 12 characteristics its empirical nature its ability to be tested the extent to which it can be falsified or disproved the ability to relicate or repeat findings the public nature of findings its self correcting nature the ability to measure or observe the phenomenon of interest the ability to minimize error through the control of procedures its level of objectivity the skepticism it raises the generalizability of findings and its heuristic nature Adopting a methodology and using it without regard to it appropriateness or e quotectiveness in answering the research question or hypothesis is known as the law of the hammer Questions suitable for communication research may be questions of fact questions of variable relations questions of value or questions of policy Nt 5 0 P l 90 o N K N Q N N N U 4 Chapter 2 The Research Process Getting Started Deductive when the researcher is moving from a known or assumed position supported by a theory to the particulars of the data Inductive when the researcher is moving from the speci cs of the data to the more general explanation of theory Summary 1 2 0 91 5 l 90 N N 0 N Q 39 N N K QM kw N 1 Researchers seek answers to questions Library research can reveal if the answer to your question is available but not known to you If the answer is neither known nor available then research must be conducted to uncover the answer Research can be an inductive or deductive process The steps of the deductive process are identifying the research problem reviewing existing theory formulating a research question or hypothesis designing the methods and procedures gathering data and analyzing and interpreting data The steps of the inductive research process are identifying the research problem considering existing research findings developing the research question designing the methods and procedures gathering data analyzing and interpreting data and developing a theoretical explanation Both the inductive and deductive research processes are circular and cyclical as the final step asking new questions starts the research process once again The first step in both the deductive and inductive research processesiidenti ing the research problemiconsists of identifying the topic of issue turning the topic into a preliminary question or set of questions conducting a library search and adjusting the question if necessary Evaluate your preliminary questions for their underlying assumptions completeness and clarity prior to conducting the library search Use the basic or detailed search strategy to find scholarly aarticles published in academic journals or scholarly books When you find an article or book that may be helpful take notes and document all of the citation information Your preliminary question may require adjustment as you discover new information The abstract states the primary ideas presented in an article or chapter The literature review usually concludes with the researchers research questions and hypotheses The discussion section includes the answers to the questions the authors raised Using what you found in the library search organize your material by major and minor points in chronological order by answering a series of questions or from the general to specific or from the specific to the general Theory is developed and tested through research Chapter 3 Introduction to Quantitative Research Concept Represents a number of individual but related things Conceptual Scheme In some cases a set of concepts can be connected together to form this For example a researcher could identify ways in which consequence is demonstrated in primetime television dramas for example characters admit guilt and take r quot quotquoty deny quot quotquot assign quot quotquot to others and so on r r Construct The theoretical de nition of a concept Concepts can become constructs only when they are linked to other concepts Variable researchers use this term to identify the theoretical construct as it is presented in research questions and hypotheses Operationalization researchers use this term to denote how the variable is observed and measured Research Hypotheses for Quantitative Research Directional Hypothesis A precise statement indicating the nature and direction of the relationship or difference between the variables Nondirectional hypothesis States that a difference will occur but does not state the direction of the difference Null hypothesis The statistical test is performed on the null hypothesis or the implicit complementary statement to the research hypothesis Idenpendent Variables Idenpendent Variables variables manipulated by the researcher In some research reports independent variables are referred to as antecedent variables experimental variables treatment variables and casual variables Predictor Variable There are some cases however in which the researcher cannot directly control manipulation of the independent variable The term should be used in descriptive research designs for example survey research Dependent Variable in uenced or changed by the independent variable Sometimes in descriptive research designs the terms criterion variable and outcome variable identify the dependent variable Intervening Variable an element that is presumed to explain or provide a link between two variables Confounding Variable A variable that confuses or obscures the effect of the independent variable on the dependent variable is said to confound the relationship Reliability is achieved when researchers are consistent in their use of data collection procedures and when participants react similarly to them Validity is achieved when the measurement does what it is intended to do Summary Quantitative research relies on the use of numbers as a way of observing and measuring communication phenomena Researchers bring objectivity to the study of communication through the use of traditional quantitative approaches and statistical techniques Quantitative research relies on deductive reasoning The primary objective of quantitative research is to test propositions developed from theory The quantitative research model includes five components research purpose literature foundation research questions and research hypotheses research methods and validity and reliability Quantitative research requires that every phenomenon studied be conceptualized and then explicitly defined Researchers work from concepts to constructs to variables to operationalizations in providing the degree of objective specificity needed to examine communication phenomena Quantitative research typically relies on the use of hypotheses to drive the research process Although researchers develop research hypotheses the null hypothesis is actually the focus of the statistical test A hypothesis includes both dependent and independent variables N 5 PI 0 l 90 o Chapter 4 Introduction to Qualitative Research Discourse naturally occurring talk or gestures is captured in a variety of forms and remains as it occurs Subjectivity Qualitative research aims for subjectivity rather than objectivity This means that researchers use interpretive research processes to make the subject of the interpretation meaningful Intersubjectivity the social accomplishment of how people coconstruct and co eXperience the interaction of social life and their rules for doing so Inductive analysis the reasoning used by qualitative researchers to discover and develop theories as they emerge from the data Triangulation The use of several kinds of methods or data to bring credibility to their ndings Data Triangulation By using a variety of data sources in one study researchers are more con dent about their ndings and conclusions Investigator Triangulation When several different reserachers or evaluators participate in the research researchers have greater con dence in their ndings because no result is dependent on one person s observations or interpretations Interdisciplinary triangulation is possible when researchers from a variety of disciplines work together on a research project Member validation or member check the process of taking the research ndings back to individuals from who data were collected or were observed There are Three Ways in which researchers interpret meaning in qualitative research Researcher Construction From his or her personal subjective position or perspective on the experience the researcher develops an interpretation Thus evidence is fully the construction of the researcher This would be the position a researcher would have to take if he or she were unable to communicate directly with the research participants As a result the researchers write the qualitative research report using their perceptions and insights Subjective Valuing this interpretation relies on tangiable artifacts which are believed to be accurate representations of the phenomenon Subjective valuing acknowledges that there are tangiable artifacts or objective sources of meaning However the researcher must make some interpretation of these objective elements With this tupe of meaning construction the researcher would miX his or her interpretations with interpretations received directly from participants Contingent Accuracy relies on tangiable artifacts which are believed to be accurate representations of the phenomenon This is the most objective of the three positions However some subjectivity is introduced when the researcher selects some elements over others to use as evidence Thus if direct quotes from research participants are available and the researcher selects the ones that require the least additional interpretation then contingent accuracy has been achieved Chapter 5 Research Ethics Bene cence means that the wellbeing of participants is protected The researcher must protect the participant from harm as well as meet the obligation to maximize possible bene ts while minimizing possible harms Respect for Persons involves two separate principles ltreating individuals as capable of making decisions and 2 protecting those who are not capable of making their own decisions Institutional Review Boards IRBs or Human Subjects Review Committees universities require their faculty and students to develop and submit a research proposal for the board s or committee s approval before any data are collected Informed Consent This means that a potential participant agrees to participate in the research project after he or she has been given some basic information about the research process Confederate a type of deceptive practice someone who pretends to also be participating in the research project but it really helping helping the researcher Anonymity means that names and other pieces of information that can identify participants are never attached to the data and sometimes are never known to the researcher Con dentiality means that any information the participant provides is controlled in such a way that others do not have access to it Chapter 7 Sampling Significance Levels and Hypothesis Testing Population consists of all units or the universeipeople or thingsipossessing the attributes or characteristics in which the researcher is interested Sample a subset or portion of a population Census used to refer to the complete count of the population Sampling Frame the set of people that have a chance to be selected must be created Practically this is a list of the available population in which you are interested and from which participants are selected Biased to favor one attribute or characteristic of the population more than another Generalizability the extent to which conclusions developed from data collected from a sample can be extended to the population Replication basing their studies on other studies that have investigated the same topic 0 Literal replication repeating the exact procedures of a previous study 0 Operational replication they attempt to reconstruct the procedures used previously 0 Constructive replication subsequent studies focus on the same constructs or variables but use different sampling techniques different populations from which to pull samples and different research procedures and measures Probability sampling a statistical bias and the most rigorous way for identifying whom to include as part of a sample Random When the probability for selection is equal it is said to be random Sampling error sometimes referred to as the margin of error the degree to which a sample differs from population characteristics on some measurement Con dence Level the degree of accuracy in predicting the result for the population from the result of the sample Con dence Interval Simple Random Sampling every person has an equal chance of being selected to participate in the study Individuals are selected one at a time and randomly Systematic Sampling Second type of random sampling You need to determine the number of entries of the population or the sampling frame and assign a unique number to each element in the sampling frame Strati ed Random Sampling In this technique the population is divided according to subgroups of interest or homogeneous groups The elements are randomly selected from each homogeneous subgroup of the population with respect to its proportion to the whole This technique is possible because lists of people or elements are available with the stratification information the researcher needs This sampling technique ensures representativeness for each of the subgroups of interest The goal of this sampling technique is to first create homogeneous subgroups and then randomly sample from each of them proportionately Cluster Sampling a twostage or multistage process The rst stage is accomplished when you can identify the population by groups or clusters In the second stage you use simple random sampling in each cluster to select your sample There is an inherent strength and weakness to this sampling technique It captures the diversity of the population but it also increases sampling error Usually cluster sampling is used because it is cheaper and easier than waiting to develop or purchase a full listing of the population which of course is sometimes impossible Nonprobability sampling sampling that does not rely on any form of random selection Although the use of nonprobability samples weakens the sample in regard to population representativeness these samples are commonly used in communication research when no other sampling technique will result in an adequate and appropriate sample Nonprobability sampling is also used when researchers study communication variables that are believed to be generally distributed through a population Researchers use nonprobability sampling because they desire research participants with some special experience or communication ability Convenience sampling the researcher simply selects those people who are convenient to him or her as respondents This can be a major disadvantage particularly if you are seeking individuals who possess traits or characteristics similar to your traits and characteristics Volunteer Sampling nonrandom sampling the researcher relies on individuals who express interest in the topic or who willing to participate in research Initially you may believe that it is best for people to volunteer to be part of your study Logistically their volunteering may expedite the research process Inclusion Criterion identifies the people or elements that meet some specific characteristic Exclusion Criterion rules out people or elements from participating in your survey or study based on some specific characteristic Snowball Sampling a nonprobability sampling technique is used when participants help researchers obtain their sample by identifying other similar participants Network Sampling unlike snowball sampling this does not rely on research participants for help in identifying the sample Rather the researcher actively solicits individuals who t a speci c pro le and asks them to participate in the research study Purposive Sampling When researchers want to select cases that are typical of the population of interest they use this sampling method which depends on the judgment of the researcher who handpicks the cases to be included inn the sample Purposive sampling is r39 39 J r J on the 39 s ability to know what is typical Purposive sampling is often used when sensitive topics are of research interest or very specialized populations are sought Quota Sampling the researcher uses the target or quota as a goal for seeking people or elements that t the characteristics of the subgroup Once the researcher meets the quota for each subgroup data collection is complete Researchers use the following steps to select a quota sample As in strati ed sampling the population is divided into subgroups that do not overlap The subgroups must be mutually exclusive That is a person or element should not be a member of more than one subgroup The number of elements in the subgroup is calculated as a proportion of the total population Once sample size is decided then a proportional number of cases or elements from each subgroup becomes a target number of cases to ll Sample Size the number of people from whom you need to observe or collect data to obtain precise and reliable ndings Population Validity the degree to which the sample represents and can be generalized to the population exists Probability an estimate of what would happen if the study were actually repeated many times telling the researcher how wrong the results can be In other words probability is a calculation about the validity of the results Statistical Inference Accepting the conclusions derived from the sample and assuming that those conclusions are also applicable to the population Probability level or Signi cance level which is established for each statistical test used prior to computing that statistical test is the level of error the researcher is willing to accept You will nd this symbolized in written research reports as the letter p or referred to as the alpha level Social Signi cance Achieving statistical signi cance does not guarantee social signi cance How the results might actually be applied or used in everyday life Type I error when the null hypothesis is rejected even when it is true The level of Type I error is set or controlled by the researcher when he or she chooses the signi cance level for the statistical test Often called the alpha level it is the same as the level of signi cance described earlier Type II error occurs in the opposite case Now the level of signi cance is not met Thus researchers simultaneously fail to reject or they accept the null hypothesis and reject the alternative hypothesis Type II error results when the alternative hypothesis is rejected even when it is true One way the researcher can control the level if Type II error is to increase the sample size Communication Research Exam 2 Chapters 69 13 Chapter 6 Measurement pg 96 0 Measurement is most often associated with quantitative methodologies and observation is most often A with 1 quot J 39 39 Measurement is a useful process because it aids researchers in identifying and presenting information about communication behavior It is the link between the conceptual and the empirical Also allows us to evaluate what is described Measurement a process that includes everything the researcher does to arrive at the numerical estimates Thus measurement includes the measuring device or instrument how the device or instrument is used and the skill of the person using the device or instrument as well as the attribute or characteristic being measured 0 Measurement can also be the process of assigning a person event or thing to a particular category 0 Why measure communication phenomena 0 Choosing a way to measure something standardizes how the variable is perceived treated and handled and in essence provides the operationalization of the variable When variables are operationalized or standardized they can be used in three types of comparisons I The first type comparison entails comparing many measurements ofthe same variable The second type comparison is especially important to researchers because science is a process of extension and replication The third type comparison allows researchers to make more distinct discriminations among elements that might appear to be similar In making these 3 types of comparisons 9 measurement allows researchers to use mathematical techniques to verify the existence of some phenomenon as well as give evidence to the existence of relationships among communication phenomena 0 Generally researchers refer to two types of measurementidiscrete and continuous Each produces a different kind of data 0 If data only name or identify what is being measured then data are discrete This level of data is referred to as categorical or nominal data 0 If data represent the value of elements then they are referred to as continuous level data Ordinal interval and ratio are three levels of continuous level data Both discrete and continuous level data are regularly collected and reported in communication research 0 I DISCRETE DATA 0 In this case data represent the presence or absence of some characteristic Group similar elements together Nominal Data or Categorical Data discrete data describe the presence of absence of some characteristic or attribute In other words the data give a name to the characteristic without any regard to the value of the characteristic 0 Examples sex political affiliation class level and employment status are measured on a categorical level The characteristic is present or absent because there is no practical way to express partial presence of the characteristic Another aspect of categorical data is that the category levels within a particular variable possess no inherent value Any value imposed on categories is arbitrary To avoid biasing responses or to avoid the appearance of a preferred response researchers frequently arrange categories alphabetically To be both a valid truthful and reliable consistent measurement the categories of a nominal variable need to be representative of the people involved Therefore categories must be Mutually exclusive people should not be able to identify themselves in more than one category Exhaustive representing the variety of characteristics of the people involved Equivalent equal to one another Finally a nominal variable must have at least two categories otherwise ali erentiation is not possible 11 CONTINUOUS LEVEL DATA Continuous Level Data or Quantitative Data Variables that take on or assume a quantity intensity or magnitude Values can differ in degree amount or frequency and these differences can be ordered on a continuum 0 Example A person s score on a questionnaire is continuous level data because a score can range from some minimum to a maximum quantity Ordinal Data Ordinal means in order Data measured in logical order from high to low or low to high Ordering suggests that there is some sequence to the value of data Yet this sequencing of data can occur without precise measurement and without knowing to what degree data are lower or higher than one another 0 There are three important things to remember about ordinal data 0 First ranking positions are only relative to the other ranking positions in that group As a result even a participant who has low preferences for all the choices presented will rank one of the lowpreference choices as having the highest ranking 0 Second the distance between ranked elements is uneven and often unknown 0 Third because ordinal data consist of relative rankings zero cannot exist Interval Data data measured based on specific numerical scores or values When using interval data we can identify which participants scored highest and lowest and we can determine the exact difference between and among scores Interval The distance between any two adjacent or contagious data points Intervals are assumed to be equal 0 An important element of interval data is the acknowledgement of zero Although this zero is arbitrary these two properties allow us to use interval data in mathematical operations Impossible to obtain a zero from a questionnaire Likert Type Scales one type of interval scale measurement that is widely used in communication research is the Likert Researchers are given a statement and then asked to respond by indicating the degree to which they agree or disagree with the statement Semantic Differential Scale Another interval measurement Using a stimulus statement participants are asked to locate the meaning they ascribe to a stimulus The response scale is anchored by two opposites usually bipolar adjectives pg 103 Ratio Data Similar to interval data except that zero is absolute This means not only that intervals between data points are equal but also that if the score is zero there is a complete lack of this variable Ratio measurement is not common in communication research When used it provides a measurement of the degree to which something actually exists 0 Example Capturing the length of interaction by audio or videorecording the conversation Noting the length of the conversation in minutes and seconds would be a ratio measurement as time has equal intervals and a true zero III VALIDITY Validity it measures what you want it to measure and not something else 0 Internal Validity Because we often cannot be absolutely certain that measuring devices capture what was intended and only what was intended validity is a matter of degree These types of issues are known as internal validity because the accuracy of conclusions drawn from the data depends upon how the research is designed and the data collected Thus internal validity addresses the relationship between the concept being measured and the process for measuring it Face Validity a measure has face validity if the items reference the construct we want to measure In essence face validity exists if the measurement looks and feels as if it will capture the construct we want to measure Although face validity is the easiest to establish most researchers would agree that it is the weakest type of validity 0 Example the Personal Report of Communication Apprehension or the PRCA24 Content Validity The degree to which the items in the measuring device represent the full range of characteristics or attitudes associated with the construct of interest is a measurement s content validity In other words the measuring items are representative of all of the items potentially available Using the PRCA content validity is achieved if its 24 items represent the complete range of verbal and nonverbal 39 39 39 39 A with 39 im apprehension Criterion Related Validity is achieved when one measurement can be linked to some other external measurement This can be achieved through two procedures predictive validity and concurrent validity o If participants scores from the two measurements are highly related or correlated concurrent validity has been achieved o Predictive validity This type of validity is often the most central concern because communication researchers want to be certain that participants responses to a questionnaire will in fact predict their communication behavior Construct Validity Researchers rely on this to assure themselves that they are measuring the core concept that was intended to be measured and not something else Often researchers use a different measure of the same or similar phenomena to establish construct validity Construct validity rests on the arguments and supporting evidence provided they are consistent with theoretical expectations IV RELIABILITY Reliability of a measurement is its degree of stability trustworthiness and dependability If a measuring device varies randomly there will be greater error and reliability will be lower Consistency is another word often used to describe reliability A reliable measure is one that is consistent that gives very similar results each time it is used Reliability Coef cient Rather than use phrases like completely reliable and not reliable at all researchers use this a number between zero and one to express how reliable their measures are The closer the reliability coef cient is to 100 the greater the degree of reliability The closer the reliability coef cient is to 0 the less the degree of reliability What is reliable enough Generally communication researchers agree that a reliability coef cient of 70 or above is acceptable 0 Internal Reliabity The degree to which the 24 items invoke the same response from the person responding to the questionnaire When there are several raters or evaluators the measure of reliability is known as interrater reliability interrater agreement or intercoder reliability This type of reliability should be reported when two or more coders assign communication behaviors to categories or when two or more raters evaluate some communication act on a scale or index Interrater reliability must be calculated for two types of content coding decisions The rst is unitizing reliability or the degree to which two or more observers agree that communication action has taken place and can identify the action in the stream of interaction 0 Once units are agreed upon then coders have to categorize or discriminate among them by assigning each unit to one of the available categories 0 Thus categorizing reliability is the second type Unitizing reliability captures the degree to which coders consistently identify what is to be coded Categorizing reliability captures the degree to which multiple coders make similar distinctions in assigning data to categories Cohen s Kappa A measure of interrater reliability for categorical data The reliability measure ranges from perfect agreement 10 to agreement that is no better than would be expected by chance 00 Scott s pi Holsti 1969 was used to calculate intercoder reliability The coders had complete agreement about the product types being advertised and the settings ie work home other indoors and outdoors Test Retest Reliability calculate the relationship or correlation between scores at two administrations of the same test or measurement to the same participants Split half reliability To avoid bias construct one test split into 2 parts thus the researcher would have two separate but equal versions of the same information Mortality participants drop out of the study simply because they are no longer members of the group being observed or attrition Attrition can also occur because paiticipants lose interest or lack the motivation to remain with the study Maturation participants are likely to change or mature over the course of observations Issues of Sample Representativeness External validity Some validity concerns are raised by the way in which researchers nd and select their samples The threat weakens the generalizability of the ndings Ecological Validity form of external validity When researchers use students as research participants because it doesn t affect any population except the students Chapter 13 Quantitative Analysis of Text Content Analysis integrates both data collection method and analytical technique as a research design to measure the occurrence of some identi able element in a complete text or set of messages Manifest content this method can be used to provide a description of the characteristics of the content itself Or content analysis can be used to study the latent content 7 interpretations about the content that imply something about the nature of the communicators or effects on communicators Unit of analysis the discrete thing that is coded and counted It is an observable and measurable unit that provides a standard way of dissecting the text into elements to be analyzed Without a standard or uniform unit the analysis will be awed because comparisons will be either impossible or meaningless Coding Reliability First intercoder reliability is established for coders abiklity to identify and agree upon the unit of coding This is known as unitizing reliability If the unit to be coded is a sentence then agreement should not be too much of a problem Natural units like complete sentences have standardized identifiers for marking their behinning and ending But if the text is naturally occurring conversation and the spreakers do not speak in complete sentences then identifying the unit to be coded is far more difficult The more frequently coders choose the same category the greater their degreee of coding or categorizing reliability There are several formulas for determining degree of intercoder or interrater reliability in coding content Scott s pi is commonly used in communication reseach when two coders are used because it accounts for the number of categories in the coding scheme as well as for the probable frequency for each category Validity In content analysis validity referws to the appropriateness and adequacy of the coding scheme for the text or messages being coded Semantic Validity to what degree do the analytic categories of the content coded have meaning for individuals in a particular context First order linkages doing so moves content analysis beyond a simple coding of messages to link their findingsiinformation they coded and counted from the websites Interaction analysis like content analysis codes of communication into categories However interaction analysis codes the content of ongoing communication between two or more individuals Thus the focus of interaction analysis is to identify the verbal or nonverbal features or functions of the stream of conversation


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