Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Assessing sentiment segregation in urban communities

Lin, YR (2014) Assessing sentiment segregation in urban communities. In: UNSPECIFIED.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

In this work, we attempt to examine the relationship between the social antecedents of urban neighborhoods and the citizens' everyday sentiment expression left in social media. Using Twitter users' geocoded messages posted within neighborhoods in the city of Pittsburgh, we first construct sentiment profiles for each neighborhood. We identify neighborhoods with relatively stable sentiment profiles and analyze the correlations between their sentiment orientations and the neighborhoods' demographic attributes including age, public safety, education, and ethnicity. The first order correlations show an interesting association between these neighborhood attributes and particular types of sentiments. We further group neighborhoods with similar demographic characteristics and observe that between two demographic groups, sentiments diverge in several sentiment categories including joy and disgust. This paper presents empirical evidence of sentiment segregation corresponding to the neighborhood contexts, which has implications for monitoring public attitudes and community integration.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Lin, YRYURULIN@pitt.eduYURULIN
Date: 1 January 2014
Date Type: Publication
Journal or Publication Title: ACM International Conference Proceeding Series
Volume: 2014-A
Event Type: Conference
DOI or Unique Handle: 10.1145/2639968.2640084
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781450328883
Date Deposited: 23 Jun 2014 21:47
Last Modified: 01 May 2019 14:02
URI: http://d-scholarship.pitt.edu/id/eprint/22032

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item