Assessing the Affective Aspect of Languaging:
The Development of Software for Public Relations
by
Gregory Neff, Purdue U, Hammond, IN, USA
219 989.2465WK
gneff@purdue.edu
Bonita Neff, Valparaiso U, Valparaiso, IN, USA
219 464-6827WK
Bonita.Neff@Valpo.Edu
Paul Crandon, Northwest Missouri State U, Maryville, MO
660 562-1827WK
crandon@mail.nwmissouri.edu
Paper prepared for refereed panel on The Impact of Technology on Public Relations
For the Division of Public Relations
International Communication Association
Seoul, Korea
July 18, 2002
Assessing the Affective Aspect of Languaging:
The Development of Software for Public Relations
Preface
The goal of this research establishes the utility of having software available to conduct research on connotative meaning and to expand the variety of applications of this analysis to further the development of communication analysis.
Research previously conducted focused on the applications such as framing and agenda setting. In this study there is much more interest in expanding the research to areas comparing words to visuals, communication management, as well as interpersonal communication.
The meaning of words often relies heavily on the innotation. Often instruments like the semantic differential are utilized to measure the affective interpretation of words, including the meaning given words in the context of a passage.
Meaning is a rich variety of possibilities. Interpretation varies for each person. The study by Crandon (Crandon, 2000) is the initial impetus for the study presented here. Literally this study is an extension of his work. The effort to establish scales and measures of affective meaning were outlined based on the Dictionary of Affect in Language developed by C.K. Whissell. On the basis of this dictionary, a program on a mainframe at Whissell’s university was developed to apply the contents of the dictionary to the context of two messages—changed only in connotative meaning.
Semantic Differential. The DAL dictionary was created by utilizing Osgood’s semantic differential scales to "rate thousands of words in terms of two important factors: the words’ pleasantness and their arousal levels" (Ibid). The goal was to work with the words selected in the Crandon study and represented "nearly 10,000 words" (Ibid). Crandon goes on to describe the usefulness of such a study:
The usefulness of such an instruments should be quite apparent: researchers could use Whissell’s dictionary to measure the tone of large quantities of copy instantly, comparing publications alone and to each other, and across time. Studies could use those methods to examine the emotional tone with which a particular issue is portrayed by different media and whether that tone changes over time. Political speeches could be analyzed for changes in emotion from one to the next or from speaker to speaker. One could compare the tone o coverage from local media versus national media, for example, or analyze coverage from a single source over the life of an issue. Studies in public relations could look at the tonal value of an in-house newsletter compared with mainstream media (Are newsletters more pleasant than "real" news?). Advertising scholars and executives could examine trend in the field and study the efficacy of ads using different tonal values. Provocative questions could be probed—How has coverage of AIDS changed in tone from the early 0s to today? Are the news media becoming more arousing in their coverage? Less arousing? Does coverage of the Gulf War differ in tone from coverage of Vietnam or other military actions? (Ibid).
Currently, one may be interested in measuring the tone of the nation from pre to post 911. The ongoing thought Americans have changed in the tone of their conversation, perhaps forever.
The interest here, however, is similar to Crandon’s in the interest for determining the "effects" of words; especially the affective tone effect on one’s interpretation. There are several approaches to this discussed by Crandon including framing as in news reporting as well as suggesting ads or poems. Most interesting is the effect of the affective tone on decision making especially when "language only and not the facts, was manipulated" under risk communication conditions (Crandon, 2000). The conclusion is it the affective tone not the "loss or gain" that results in a decision. Thus this study offers another opportunity to substantiate these findings and provide other venues for discovering how the effect of affective tone works.
Further Background
While Crandon covered the research primarily outside the communication field, this update provides a perspective found more closely aligned to the communication documentation for affective meaning. In examining the communication journals organized by the National Communication Association, Priscilla Murphy established in The Journal of Health Communication three policy frames examining text from industry, government, and lay activists on the topic of tobacco. The idea being that to study samples from these text frames, one could establish if the affective meaning is similar or quite varied. What is interesting is the uniqueness of this research indicating how each groups discourse "revealed discourse patterns peculiar to each group and reflective of their cultural biases toward health risk" (Murphy, 2001). What could be done with this study is to apply the software to the words used in each policy frame to test if interpretations varied and/or the affective tone changed. Such an application of this software database could provide a richer sense of how each participant is viewed and ultimately change the approach to negotiation. Even more important is adding in the "cultural element" to the affective interpretation, especially with the different philosophies, competing paradigms, and ethnic groups involved in issues today.
Another dimension is the degree to which society is becoming more and more visually oriented. In High Culbertson’s article on "Words vs. Pictures: Perceived Impact and Connotative Meaning" the idea of words carrying the affective weight of a picture is an interesting concept. This involves obviously including the visual as one variable and comparing the competing message scenarios carrying the affective meaning. Again, measuring the similarities and differences is critical to the measurement of meaning and may demonstrate how words can be powerful or effective in bringing about a particular type of interpretation.
Dictionary Application
Crandon outlines several uses of Whissell’s dictionary including analyzing which songwriter is more happy, including "how the mood of the lyrics changed over time" (Crandon, 6). Ads "directed at men were more arousing and less pleasant than the ads aimed at women" (Ibid). Lastly, analyzing newspaper headlines and journal article titles for sensationalism provided a means for measuring standards in various disciplines.
Purpose of Study
This study replicated the earlier Crandon study utilizing a mainframe by developing and adapting software usable by anyone. Working with Microsoft Word, a spell check approach is developed based on the DAL dictionary. The database of words and scores focused on the scales of pleasantness and arousal levels. The scales are alternately called evaluation and activation. The affective tone of Crandon’s two texts is measured here statistically to compare these bodies of text for affective tone.
Installation and Operating Instructions
To install the software, download and copy the files normat.dot from the link http://technology.calumet.purdue.edu/met/gneff/Publications/ica02/normal.dot and Dictionary of Affect in Language.doc from http://technology.calumet.purdue.edu/met/gneff/Publications/ica02/DAL.doc. Put these files into the templates directory identified on the File Locations tab of the Options item under the Tools pull down menu of Microsoft Word. The software will analyze either a selection of a document if part of a document is selected or the whole document if nothing is selected. The mean scores for pleasantness and arousal on a 1 to 3 point scale are given in a message box. A score of one would correspond to a low pleasantness or arousal value, two would correspond to a medium or average value and three to a high value. For a more detailed analysis than the message box, open the file results.txt in the same directory as the templates and the DAL. This file is written over each time the macro is run. To run the macro either click on the Normal.NewMacros.Affect button or select the Affect Macro in the Macro item of the Tools pull down menu of Word. If your computer system uses another version of Word than Word 2000 it may be necessary to import the macro code affect.bas from the link http://technology.calumet.purdue.edu/met/gneff/Publications/ica02/Affect.bas into a module inserted into the normal.dot template. Email the first author of this paper if you need assistance.
Two Texts Compared with the Software
Local water company discovers bacteria
PIKEVILLE, Ky. (UPI) Residents of a rural district south of Pikeville, Ky., will receive an announcement in the mail this week to advise them of potentially undesirable coliform bacteria discovered in their local water supply.
Pikeville Utilities director William Burke said that existing levels of the bacteria, revealed after a recent analysis are more than twice the limit set by the Environmental Protection Agency.
The Department of environmental Quality required that communities be informed when impurities go above state supported levels.
The affected area includes close to 80 households near Chloe, Ky., and Shelbiana, Ky., that once received water from Millstone Water Co.
The City of Pikeville took over the Millstone system last year and began getting water from Carr Creek Water Co. to help meet the need of families in the neighborhood.
While water drawn from underground sources remains relatively pure, much of the water supplied by community providers still comes from surface water.
Sources such as rivers and reservoirs bear a greater chance of Contamination from bacteria and parasites-commonly the result of refuse from livestock and pasture runoff.
Still, the underground aquifers are not always carefree when it comes to the effort for clean water. "It’s not unusual for these bacteria to be found in the upper levels of the shallow aquifers we have in this part of the country," Burke said.
He also attributes matters to water systems’ increasing reliance on aging pipes and inadequate treatment equipment to make the water safe to drink.
This year marks the 25th anniversary of the passing of the Safe Drinking Water Act.
Group I- The
"nicer" article.
Local water company finds bacteria
PIKEVILLE, Ky. (UPI) Residents of a rural area south of Pikeville, Ky., will receive a statement in the mail this week to warn them of potentially dangerous coliform bacteria found in their local water reserve.
Pikeville Utilities Director William Burke said that prevailing levels of the pollutant, found during a recent investigation are more than double the limitation fixed by the Environmental Protection Agency.
The Department of Environmental Quality requires that residents be told when impurities go beyond state adopted levels.
The concerned area includes close to 80 residences near Chloe, Ky., and Shelbiana, Ky., that once purchased water from Tankard Utilities, Inc.
The city of Pikeville took over the Tankard system last year and began purchasing water from Carr Creek Water Co. to help meet the demands of citizens in the district.
While water drawn from underground sources remains relatively clear, much of the water supplied by municipal providers still comes from surface water.
Sources such as rivers and lakes bring a greater probability of contamination from bacteria and parasites-usually the result of waste from cattle and field runoff.
Still, the underground aquifers are not always worry-free when it comes to the push for clean water. "It’s not abnormal for these bacteria to be detected in the upper levels of the shallow aquifers we have in this part of the country," Burke said.
He also blames problems on water systems’ expanding reliance on aging pipes and crude treatment equipment to make the water safe to drink.
This year marks the 25th anniversary of the passing of the Safe Drinking Water Act.
Group 2-The "Harsher" article
The analysis shows the first "nicer" article has a Pleasantness mean of 1.799 and an Arousal mean of 1.523. The second "harsher" article has a Pleasantness mean of 1.729 while the Arousal mean is 1.583. This is a small difference although the "harsher" article is slightly less pleasant and slightly more arousing on the scale as expected. In the Crandon study the "harsher" article was prepared from the "nicer" one. "Words were selected," according to Crandon "for manipulation based on the presence of a synonymous alternative in the DAL that could serve as its counterpart…substituting more pleasant and less arousing words for their opposite." Only 43 words were changed from one article to the other. There were approximately 235 words in each article which appeared in the DAL out of the total of 261 words.
When 348 students were given one of the two articles, there was a significant difference in their perception of risk based on whether they read the "harsher" or "nicer" article when it came to how they thought others would feel. This is suggestive that small differences in the pleasantness or arousal means may be perceptible.
References
Crandon, P. (2000). Risk Communication: the Importance of Affective Tonal Value and Perceptions of Risk". Paper presented at the annual meeting of the International Communication Association for the Public Relations Division for the refereed panel on Public Relations: Social Responsibility in a Complex Age, Acapulco, Mexico, June 1-5, 2000.
Culbertson, Hugh M. (1974). Words vs. Pictures: Perceived Impact and Connotative Meaning. Journalism Quarterly, Vol. 51, Summer, 226-237.
Murphy, Pricilla (2001). Framing the nicotine debate: A cultural approach to risk. Health Communication. 13 (2),. 119-140.
Osgood, C.E., Suci, G. J., Tannenbaum, P.H., Measurement of Meaning (Urbana: University of Illinois Press, 1957).
K. Sweeney and C. Whissell, A Dictionary of Affect in Language: I. Establishment and Preliminary Validation," Perceptual and Motor Skills, 59 (1984): 695-698.
C. Whissell and K. Charuk, A Dictionary of Affect in Language: II. Word Inclusion and Additional Validation, Perceptual and Motor Skills, 61 (1985): 65-66.
Appendix I Macro Code
Attribute VB_Name = "NewMacros"
Public thisRange As Variant
Public nWords, thisWordIndex As Integer
Sub Affect()
Attribute Affect.VB_Description = "Macro
recorded 7/25/2002 by G. Neff at Purdue University Calumet"
Attribute Affect.VB_ProcData.VB_Invoke_Func =
"Normal.NewMacros.Affect"
' Affect Macro to do a semantic differential
analysis on a document or selection
' Macro version 7/10/2002 by Gregory Neff at Purdue
University Calumet
Open "Results.txt" For Output As #1
If Selection.Type = wdSelectionIP Then
Set thisRange = ActiveDocument.Content
Else
Set thisRange = Selection.Range
End If
thisWordIndex = 0
nWords = CStr(thisRange.Words.Count)
Dim Pleasant(10000) As Single
Dim Arousal(10000) As Single
iWords = 0
PleasantTotal = 0
ArousalTotal = 0
Print #1, thisRange
Print #1, "nWords= "; nWords
MyDocument = ActiveDocument.Name
Documents.Open FileName:="DAL.doc",
ReadOnly:=True
'Dictionary of Affect in Language or DAL.doc
complements of C.K. Whissell
For Index = 1 To nWords
Call WordSelectorForward
TrialWord$ = Selection
TrialWord$ = RTrim(TrialWord$)
Print #1, TrialWord$
If TrialWord$ = vbNewLine Then GoTo Endloop
If TrialWord$ = vbCrLf Then GoTo Endloop
If TrialWord$ = vbLf Then GoTo Endloop
If TrialWord$ = "." Then GoTo Endloop
If TrialWord$ = "." & vbNewLine Then
GoTo Endloop
If TrialWord$ = "." & vbCrLf Then
GoTo Endloop
If TrialWord$ = "." & vbLf Then GoTo
Endloop
If TrialWord$ = "," Then GoTo Endloop
If TrialWord$ = "" Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
If TrialWord$ = " " Then GoTo Endloop
Documents("DAL.doc").Activate
Selection.Find.ClearFormatting
With Selection.Find
.Text = TrialWord$
.Replacement.Text = ""
.Forward = True
.Wrap = wdFindContinue
.Format = False
.MatchCase = False
.MatchWholeWord = True
.MatchWildcards = False
.MatchSoundsLike = False
.MatchAllWordForms = False
End With
Selection.Find.Execute
If Selection.Find.Found = True Then
iWords = iWords + 1
Selection.MoveRight Unit:=wdWord, Count:=1
Selection.MoveRight Unit:=wdCharacter, Count:=6,
Extend:=wdExtend
PleasantValue = Val(Selection)
If PleasantValue = 0 Then GoTo Endloop
PleasantTotal = PleasantTotal + PleasantValue
Pleasant(iWords) = PleasantValue
Selection.MoveRight Unit:=wdWord, Count:=2
Selection.MoveRight Unit:=wdWord, Count:=3,
Extend:=wdExtend
ArousalValue = Val(Selection)
ArousalTotal = ArousalTotal + ArousalValue
Arousal(iWords) = ArousalValue
msg1 = "Pleasantness: " &
CStr(PleasantValue)
msg2 = " Arousal: " &
CStr(ArousalValue)
msg3 = "Word Number: " & CStr(iWords)
Print #1, msg1;
Print #1, msg2;
Print #1, msg3
End If
Endloop:
Next Index
For n = 1 To iWords
Pleas1 = (Pleasant(n) - PleasantTotal / iWords) ^ 2
Arous1 = (Arousal(n) - ArousalTotal / iWords) ^ 2
Next n
'Prepare and display the results.
msg1 = "Pleasantness Average: " &
CStr(PleasantTotal / iWords)
If iWords <> 1 Then psd = " Pleasantness
Std. Dev. = " & CStr((Pleas1 / (iWords - 1)) ^ 0.5)
msg2 = "Arousal Average: " &
CStr(ArousalTotal / iWords)
If iWords <> 1 Then asd = " Arousal Std.
Dev. = " & CStr((Arous1 / (iWords - 1)) ^ 0.5)
msg3 = " Words found: " &
CStr(iWords)
Print #1, msg1;
If iWords <> 1 Then Print #1, psd
Print #1, msg2;
If iWords <> 1 Then Print #1, asd
Print #1, msg3
Close #1
Response = MsgBox(msg1 & vbNewLine & msg2
& vbNewLine & msg3 & vbNewLine, vbOKOnly, "Affect
Analysis")
Documents("DAL.doc").Close
End Sub
Sub WordSelectorForward()
'Selects the next indexed word in thisRange.
thisWordIndex = thisWordIndex + 1
wordCount = thisRange.Words.Count
If thisWordIndex = wordCount + 1 Then thisWordIndex
= 1
thisRange.Words(thisWordIndex).Select
End Sub
Appendix II First Page of the DICTIONARY OF AFFECT IN LANGUAGE
|
|
Evaluation |
Activation |
|
|
Evaluation |
Activation |
|
|
Evaluation |
Activation |
|
a |
2 |
1.3846 |
|
achievements |
2.5 |
2.727 |
|
adrenaline |
2.33 |
2.667 |
|
abandon |
1 |
2.375 |
|
achieving |
2.8 |
2.625 |
|
ads |
2.25 |
1.1429 |
|
abandoned |
1.1429 |
2.1 |
|
achy |
1 |
2.3 |
|
adult |
2.4 |
2.0769 |
|
abandonment |
1 |
2 |
|
acid |
1.25 |
2 |
|
adults |
1.8 |
1.875 |
|
abated |
1.6667 |
1.3333 |
|
acknowledge |
1.8 |
1.25 |
|
advance |
2.25 |
1.7143 |
|
abilities |
2.5 |
2.1111 |
|
acknowledged |
2.1429 |
1.5 |
|
advanced |
2.429 |
1.7 |
|
ability |
2.5714 |
2.5 |
|
acquainted |
2.2 |
1.5 |
|
advancement |
2.333 |
1.7778 |
|
able |
2.2 |
1.625 |
|
acquire |
2.2 |
1.625 |
|
advances |
2.5 |
2.1818 |
|
abnormal |
1 |
2 |
|
acquired |
1.75 |
1.7143 |
|
advantage |
2.571 |
2.1 |
|
aboard |
1.8 |
1.875 |
|
acquiring |
2.1818 |
2.0714 |
|
advantages |
2.5 |
2.0909 |
|
abolition |
1.5 |
2.1818 |
|
acquisition |
1.8333 |
1.6667 |
|
adventure |
2.833 |
3 |
|
abortion |
1 |
2.7273 |
|
acreage |
1.6667 |
1.3333 |
|
adventures |
2.667 |
2.8333 |
|
about |
1.7143 |
1.3 |
|
acres |
2 |
1.5455 |
|
adverse |
1.4 |
1.625 |
|
above |
2.2 |
1.25 |
|
across |
2 |
1.625 |
|
advertising |
2 |
2 |
|
abroad |
2.6 |
1.75 |
|
act |
1.7143 |
2.4 |
|
advice |
2.5 |
1.9091 |
|
abrupt |
1.2857 |
2.3 |
|
acted |
1.4 |
2 |
|
advise |
2.333 |
1.5833 |
|
abruptly |
1.1429 |
2.2 |
|
acting |
1.75 |
2.4545 |
|
advised |
2 |
2.1 |
|
abscess |
1.125 |
1.5455 |
|
action |
2 |
2.8889 |
|
advisee |
2 |
1.6 |
|
absence |
1.5 |
1.5556 |
|
actions |
2.3333 |
2.9167 |
|
advisers |
2 |
1.7273 |
|
absent |
1 |
1.3 |
|
active |
2.4 |
2.625 |
|
advisory |
1.571 |
1.7 |
|
absolute |
1.6667 |
1.4444 |
|
actively |
2.4286 |
2.4 |
|
advocate |
2.25 |
2 |
|
absolutely |
1.6 |
1.5 |
|
activist |
2.2 |
2.375 |
|
aesthetic |
2.167 |
1.3333 |
|
absorb |
1.8 |
1.75 |
|
activities |
2.3333 |
2.4167 |
|
affair |
1.25 |
2.2857 |
|
absorbed |
1.4 |
1.625 |
|
activity |
2.6667 |
2.4444 |
|
affairs |
1.167 |
2.3333 |
|
absorption |
1.7778 |
1.6667 |
|
actor |
2.4 |
2 |
|
affect |
1.75 |
1.8571 |
|
abstract |
1.6667 |
1.4444 |
|
actor's |
2.1 |
2.3077 |
|
affected |
2 |
1.5714 |
|
abstraction |
1.4286 |
1.4 |
|
actors |
1.8333 |
2.3333 |
|
affection |
2.778 |
2.25 |
|
absurd |
1 |
1.5 |
|
acts |
2.1667 |
2.4444 |
|
affects |
2 |
1.9 |
|
abundance |
2.6667 |
1.5556 |
|
actual |
2 |
1.25 |
|
affirm |
2 |
1.8571 |
|
abuse |
1.4286 |
2.5 |
|
actually |
1.6667 |
1.4444 |
|
affixed |
1.714 |
1.4 |
|
abusers |
1.25 |
2.7273 |
|
acute |
1.3 |
1.8462 |
|
affliction |
1.4 |
1.625 |
|
abusing |
1.25 |
2.8182 |
|
ad |
2.1667 |
1.4444 |
|
afford |
2.375 |
1.9091 |
|
abusive |
1.6667 |
2.6667 |
|
adaptation |
1.5714 |
2.2 |
|
afforded |
1.75 |
1.7143 |
|
abut |
1.7143 |
1.4 |
|
adapted |
2 |
2 |
|
afraid |
1 |
2.375 |
|
academic |
1.8 |
1.5 |
|
add |
2 |
1.7778 |
|
Africa |
2.143 |
1.6 |
|
academy |
2 |
1.625 |
|
added |
2 |
1.6667 |
|
African |
2 |
1.375 |
|
accelerated |
2.1667 |
2.4444 |
|
adding |
2.1429 |
1.9 |
|
after |
1.8 |
1.25 |
|
acceleration |
2.2857 |
2.5 |
|
addition |
1.6 |
1.375 |
|
after-thought |
1.75 |
1.4286 |
|
accept |
2.4444 |
1.5 |
|
additional |
1.8333 |
1.4444 |
|
afternoon |
2.455 |
1.4286 |
|
acceptable |
1.8889 |
1.5 |
|
addled |
1.8 |
1.375 |
|
afternoons |
2.333 |
1.5556 |
|
acceptance |
2.5 |
1.4286 |
|
address |
1.875 |
1.6364 |
|
afterward |
2.167 |
1.3333 |
|
accepted |
1.6667 |
1.3333 |
|
addressed |
1.875 |
1.6364 |
|
afterwards |
1.875 |
1.3636 |
|
accepting |
1.5 |
1.2857 |
|
addresses |
1.7143 |
1.4 |
|
again |
1.8 |
1.5 |
|
access |
2.4545 |
1.9231 |
|
adds |
2.2 |
1.5 |
|
against |
1.143 |
1.3 |
|
accident |
1 |
2.375 |
|
adequate |
2.2 |
1.5 |
|
age |
1.8 |
1.875 |
|
accommodate |
2 |
1.7143 |
|
adequately |
2 |
1.6 |
|
aged |
1.5 |
1.7273 |
|
accompanied |
2.1429 |
2.2 |
|
adjacent |
1.7143 |
1.4 |
|
agencies |
1.833 |
1.5556 |
|
accompanying |
1.8333 |
2.1111 |
|
adjoining |
1.875 |
1.6364 |
|
agency |
1.75 |
1.8182 |
|
accomplish |
2.75 |
2.3636 |
|
adjust |
1.8333 |
1.8889 |
|
agent |
1.6 |
1.25 |
|
accomplished |
2.7143 |
2.4 |
|
adjusted |
2.2857 |
1.8 |
|
agents |
1.429 |
1.4 |
|
accomplishments |
2.625 |
2.2727 |
|
adjusting |
1.5 |
1.7778 |
|
ages |
1.6 |
1.625 |
|
accordance |
2 |
1.5556 |
|
adjustment |
1.6 |
2 |
|
aggravate |
1.111 |
2.4167 |
|
according |
1.6667 |
1.6667 |
|
adjustments |
1.6 |
1.875 |
|
aggravating |
1 |
2.2222 |
|
accordingly |
1.8 |
1.375 |
|
administered |
1.2 |
1.625 |
|
aggression |
1 |
2.25 |
|
account |
1.6 |
1.5 |
|
administration |
1.8889 |
1.8333 |
|
aggressive |
1.2 |
2.6923 |
|
accounting |
1.5 |
2 |
|
administrative |
1.5 |
1.5556 |
|
aghast |
1 |
1.7778 |
|
accounts |
1.5556 |
1.75 |
|
administrator |
1.2857 |
1.7 |
|
agitated |
1.333 |
2.2222 |
|
accumulated |
1.8571 |
2.1 |
|
admirable |
2.7778 |
1.6667 |
|
ago |
1.6 |
1.1429 |
|
accumulation |
2.1429 |
1.6 |
|
admiration |
2.5 |
1.7778 |
|
agree |
2.667 |
1.8889 |
|
accuracy |
2.625 |
2 |
|
admire |
1.9 |
1.6 |
|
agreeable |
2.7 |
2.0769 |
|
accurate |
2.5714 |
2.1 |
|
admired |
2.75 |
1.8182 |
|
agreed |
2.667 |
1.7778 |
|
accurately |
2.5 |
1.7273 |
|
admission |
2 |
1.6364 |
|
agreement |
2.571 |
2 |
|
accuse |
1 |
2.2222 |
|
admit |
1.6667 |
1.6667 |
|
agreements |
2.167 |
1.6667 |
|
accused |
1 |
1.7143 |
|
admitted |
2 |
2 |
|
agrees |
2.4 |
1.625 |
|
accustomed |
2.1667 |
1.1111 |
|
adolescence |
1.8 |
1.875 |
|
agricultural |
1.8 |
1.25 |
|
ace |
3 |
1.2857 |
|
adolescent |
1.4 |
2 |
|
agriculture |
2.286 |
1.3 |
|
aced |
2.75 |
2.1429 |
|
adopt |
1.8333 |
2.5556 |
|
ah |
2.4 |
1.5 |
|
achieve |
2.8889 |
2.8333 |
|
adopted |
1.7143 |
2.5 |
|
ahead |
1.556 |
1.6667 |
|
achieved |
2.7143 |
2.8 |
|
adopting |
2.1111 |
2.75 |
|
aid |
2.2 |
1.625 |
|
achievement |
2.75 |
2.7143 |
|
adoring |
2.75 |
2.1429 |
|
aided |
2.5 |
1.7273 |