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The Secret Life of Pronouns_ What Our Words Say About Us - James W. Pennebaker [109]

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a method similar to language style matching, we were able to calculate the degree to which residents in any given town used language in similar ways. The findings suggested that the more similar the community’s use of language, the more cohesive the city.

As you look at the table that lists the ten most and least linguistically cohesive communities, the difference between them may not be immediately obvious. It’s not a matter of north versus south, liberal versus conservative, rich versus poor, or even a function of the towns’ racial makeup, age distribution, or migration into or out of the city. Rather, one of the most striking differences between the two lists is that the most cohesive communities have higher and more equal income distributions than the least cohesive. Using a statistic called a Gini coefficient, demographers can determine the degree to which wealth is spread around in any given city, state, or country. Cities where the residents use language in similar ways tend to be communities that are more similar in terms of their incomes. The bigger the split between the rich and poor of a community, the more varied their writing styles for Craigslist ads.

RANKING OF COMMUNITIES BY LANGUAGE STYLE MATCHING STATISTICS FOR CRAIGSLIST ADS

MOST LINGUISTICALLY COHESIVE (TOP 10)

LEAST LINGUISTICALLY COHESIVE (BOTTOM 10)

Portland, Oregon

Bakersfield, California

Salt Lake City, Utah

Greensboro, North Carolina

Raleigh, North Carolina

Louisville, Kentucky

Birmingham, Alabama

Oklahoma City, Oklahoma

Rochester, New York

Dayton, Ohio

Hartford, Connecticut

El Paso, Texas

New Orleans, Louisiana

Jacksonville, Florida

Richmond, Virginia

Columbia, South Carolina

Worcester, Massachusetts

Tulsa, Oklahoma

Tucson, Arizona

Albany, New York

Note: Cohesiveness is calculated by the degree to which people in the various communities used function words at comparable levels in their Craigslist ads.

You can see why the Gini statistic is important. In communities where there is a much larger split between the rich and the poor, it’s less likely that the different elements of the city will interact. As the range of income within a town becomes smaller, the residents will likely have more in common with one another and should talk more with others. Not coincidentally, they should also have more objects and services that others in the community would want to exchange on Craigslist.

The magic of this project is not about the links between income distributions and social patterns in cities. Rather, it shows how words in the most mundane of places can reveal important information about a community’s social ties. All groups, whether families, work groups, companies, or entire cities, leave trails of their social and psychological lives behind in the words their members use in communicating with each other. Words are one of the human-made elements that connect our thoughts and ideas across people. By tracking our words, we get a sense of the social fabric.

GROUP SPOTTING: HOW WORDS REVEAL WHAT A GROUP IS DOING AND WHERE IT IS

Consider what we know so far. Individuals use words—especially pronouns—to signify their sense of belongingness to a wide range of ever-shifting groups. Whereas we-ness measures reflect feelings of group identity, synchrony measures, such as language style matching, tap a shared worldview by the group members.

Taken together, the various findings point to the shared mind-set of most groups. Within any group—whether a family, school, work team, or even a community—people soon start talking alike. In small groups, they discuss the same topics with each other, and in a sense, it isn’t too shocking that their function words are similar. But as groups get larger and not everyone necessarily talks with everyone else, it is impressive that the group still maintains its own linguistic style.

Sociolinguists would not be surprised that large groups share similar linguistic styles. There is now a generation of important research tracking how neighborhoods, cities, and entire

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