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Situations in 140 Characters: Assessing Real-World Situations on Twitter.

Serfass DG, Sherman RA - PLoS ONE (2015)

Bottom Line: Females share both more emotionally charged (pOsitive and Negative) situations, while no differences were found in the amount of Duty experienced by males and females.Differences in the situations shared from Rural and Urban areas were not found.Future applications of assessing situations using social media are discussed.

View Article: PubMed Central - PubMed

Affiliation: Florida Atlantic University, Boca Raton, Florida, United States of America.

ABSTRACT
Over 20 million Tweets were used to study the psychological characteristics of real-world situations over the course of two weeks. Models for automatically and accurately scoring individual Tweets on the DIAMONDS dimensions of situations were developed. Stable daily and weekly fluctuations in the situations that people experience were identified. Predicted temporal trends were found, providing validation for this new method of situation assessment. On weekdays, Duty peaks in the midmorning and declines steadily thereafter while Sociality peeks in the evening. Negativity is highest during the workweek and lowest on the weekends. pOsitivity shows the opposite pattern. Additionally, gender and locational differences in the situations shared on Twitter are explored. Females share both more emotionally charged (pOsitive and Negative) situations, while no differences were found in the amount of Duty experienced by males and females. Differences in the situations shared from Rural and Urban areas were not found. Future applications of assessing situations using social media are discussed.

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Related in: MedlinePlus

Top: General Additive Model smoothed line for the pOsitivity and Negativity of Tweets over the course of a week (averaged across two weeks).Bottom: Mean pOsitivity and Negativity scores of all Tweets and the General Additive Model smoothed line for the predicted scores of Positivity and Negativity over the course of a week (averaged across two weeks).
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pone.0143051.g002: Top: General Additive Model smoothed line for the pOsitivity and Negativity of Tweets over the course of a week (averaged across two weeks).Bottom: Mean pOsitivity and Negativity scores of all Tweets and the General Additive Model smoothed line for the predicted scores of Positivity and Negativity over the course of a week (averaged across two weeks).

Mentions: Fig 2 shows the Generalized Additive Model Smoothed line for predicted ratings of pOsitivity and Negativity over the course of a week. The scores were aggregated by day and time to obtain the average score for each minute of each day combining the two weeks from which Tweets were sampled. Both of these curves follow the hypothesized patterns with Negativity highest throughout the workweek and pOsitivity highest over the weekend. The lower panels of Fig 2 display the average pOsitivity and Negativity scores for every minute throughout a week. This illustrates that, although average pOsitivity and Negative vary across the week, the amount of within-day variability in pOsitivity and Negativity is substantially greater than the between-day variability.


Situations in 140 Characters: Assessing Real-World Situations on Twitter.

Serfass DG, Sherman RA - PLoS ONE (2015)

Top: General Additive Model smoothed line for the pOsitivity and Negativity of Tweets over the course of a week (averaged across two weeks).Bottom: Mean pOsitivity and Negativity scores of all Tweets and the General Additive Model smoothed line for the predicted scores of Positivity and Negativity over the course of a week (averaged across two weeks).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643936&req=5

pone.0143051.g002: Top: General Additive Model smoothed line for the pOsitivity and Negativity of Tweets over the course of a week (averaged across two weeks).Bottom: Mean pOsitivity and Negativity scores of all Tweets and the General Additive Model smoothed line for the predicted scores of Positivity and Negativity over the course of a week (averaged across two weeks).
Mentions: Fig 2 shows the Generalized Additive Model Smoothed line for predicted ratings of pOsitivity and Negativity over the course of a week. The scores were aggregated by day and time to obtain the average score for each minute of each day combining the two weeks from which Tweets were sampled. Both of these curves follow the hypothesized patterns with Negativity highest throughout the workweek and pOsitivity highest over the weekend. The lower panels of Fig 2 display the average pOsitivity and Negativity scores for every minute throughout a week. This illustrates that, although average pOsitivity and Negative vary across the week, the amount of within-day variability in pOsitivity and Negativity is substantially greater than the between-day variability.

Bottom Line: Females share both more emotionally charged (pOsitive and Negative) situations, while no differences were found in the amount of Duty experienced by males and females.Differences in the situations shared from Rural and Urban areas were not found.Future applications of assessing situations using social media are discussed.

View Article: PubMed Central - PubMed

Affiliation: Florida Atlantic University, Boca Raton, Florida, United States of America.

ABSTRACT
Over 20 million Tweets were used to study the psychological characteristics of real-world situations over the course of two weeks. Models for automatically and accurately scoring individual Tweets on the DIAMONDS dimensions of situations were developed. Stable daily and weekly fluctuations in the situations that people experience were identified. Predicted temporal trends were found, providing validation for this new method of situation assessment. On weekdays, Duty peaks in the midmorning and declines steadily thereafter while Sociality peeks in the evening. Negativity is highest during the workweek and lowest on the weekends. pOsitivity shows the opposite pattern. Additionally, gender and locational differences in the situations shared on Twitter are explored. Females share both more emotionally charged (pOsitive and Negative) situations, while no differences were found in the amount of Duty experienced by males and females. Differences in the situations shared from Rural and Urban areas were not found. Future applications of assessing situations using social media are discussed.

Show MeSH
Related in: MedlinePlus