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USER REVIEW SITES AS A RESOURCE
FOR LARGE-SCALE SOCIOLINGUISTIC
STUDIES
By,
Ashutosh Bhargave.
Anders Johannsen, Dirk Hov, Anders Søgaard
University of Copenhagen
OUTLINE:
 Introduction
 Data Format
 Data Augmentation
 Representativeness
 Pilot Studies
 Conclusion
 Sociolinguistic studies
 Problems:
• Traditional approach.
• Social media data
 Remedy:
• Paper aims to remedy both problems by exploring a
large new data source, international review
websites with user profiles.
language
extra-linguistic
variables
Relation
DATA FORMAT:
• The Trustpilot Corpus consists of user reviews from the Trustpilot
website.
• Users need to register with a username in
order to leave review
• no mandatory fields other than the name
• assign unique identifiers to both users and
companies and use those to link up reviews.
• mostly interested in age, gender, and location
in combination with the written reviews.
DATA AUGMENTATION
 Augmented the retrieved data set in two ways,
1. gender information based on 1st names, and
2. geo tagging information (latitude & longitude)
 Problems -
1. no gender information
2. “canonical" town
REPRESENTATIVENESS
 restricted to the age range from 16 to 80.
 median age in our data is typically close to the
country's median value.
 more male than female users
 average number of reviews per user is around 4
PILOT STUDIES
Discovering gender-specific words :
 Emoticons, age, and gender
 Eyes ( : ; ) Nose ( - or none) Mouth ( ( , ) , [ ,* etc)
 women use emoticons almost twice as often as men do
 for all ages, the use of a nose is highly anti correlated
with age
Ratings, categories, gender, and age
 men tend to vote slightly more negative than women
 people in the younger group are more likely to use
negative ratings than people in the older group
DENMARK
 missing distinction between the reflexive possessive
pronouns and non-reflexives
 record the frequency of sin/sit (his/her own) and the
joint frequency of all possessive pronouns(his). Then
compute the ratio of the former in all pronouns.
Swear words across location, gender, and age:
• as people grow older, they tend to use more conservative language
• women use this stronger version words less than the men
GERMAN
 Replacement : β with ss
 dass/daβ, “that", and the modal mussen/muβen, “to
must”
 older speakers retain the traditional spelling they
acquired in their youth to a much greater extent .
CONCLUSION
 Traditional sociolinguistic studies often lack
statistical power to draw valid conclusions and big-
data approaches to language studies mostly lack
extra-linguistic information that would enable
sociolinguistic studies.
 Solution to this dilemma is user review sites.
QUESTIONS ?
THANK YOU

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User review sites as a resource for large scale Sociolinguistic studies

  • 1. USER REVIEW SITES AS A RESOURCE FOR LARGE-SCALE SOCIOLINGUISTIC STUDIES By, Ashutosh Bhargave. Anders Johannsen, Dirk Hov, Anders Søgaard University of Copenhagen
  • 2. OUTLINE:  Introduction  Data Format  Data Augmentation  Representativeness  Pilot Studies  Conclusion
  • 3.  Sociolinguistic studies  Problems: • Traditional approach. • Social media data  Remedy: • Paper aims to remedy both problems by exploring a large new data source, international review websites with user profiles. language extra-linguistic variables Relation
  • 4. DATA FORMAT: • The Trustpilot Corpus consists of user reviews from the Trustpilot website. • Users need to register with a username in order to leave review • no mandatory fields other than the name • assign unique identifiers to both users and companies and use those to link up reviews. • mostly interested in age, gender, and location in combination with the written reviews.
  • 5. DATA AUGMENTATION  Augmented the retrieved data set in two ways, 1. gender information based on 1st names, and 2. geo tagging information (latitude & longitude)  Problems - 1. no gender information 2. “canonical" town
  • 6. REPRESENTATIVENESS  restricted to the age range from 16 to 80.  median age in our data is typically close to the country's median value.  more male than female users  average number of reviews per user is around 4
  • 8.  Emoticons, age, and gender  Eyes ( : ; ) Nose ( - or none) Mouth ( ( , ) , [ ,* etc)  women use emoticons almost twice as often as men do  for all ages, the use of a nose is highly anti correlated with age
  • 9. Ratings, categories, gender, and age  men tend to vote slightly more negative than women  people in the younger group are more likely to use negative ratings than people in the older group
  • 10. DENMARK  missing distinction between the reflexive possessive pronouns and non-reflexives  record the frequency of sin/sit (his/her own) and the joint frequency of all possessive pronouns(his). Then compute the ratio of the former in all pronouns.
  • 11. Swear words across location, gender, and age: • as people grow older, they tend to use more conservative language • women use this stronger version words less than the men
  • 12. GERMAN  Replacement : β with ss  dass/daβ, “that", and the modal mussen/muβen, “to must”  older speakers retain the traditional spelling they acquired in their youth to a much greater extent .
  • 13. CONCLUSION  Traditional sociolinguistic studies often lack statistical power to draw valid conclusions and big- data approaches to language studies mostly lack extra-linguistic information that would enable sociolinguistic studies.  Solution to this dilemma is user review sites.