Recreating Human Mobility Patterns Through the Lens of Social Media: Using Twitter to Model the Social Ecology of Crime
Studies of neighborhood crime are often limited in their ability to account for the dynamic nature of human mobility, a central tenet of prominent theoretical perspectives on the spatial distribution of crime. Yet, recent work indicates the utility of social media data for estimating the size and co...
| Authors: | ; ; ; |
|---|---|
| Format: | Electronic Article |
| Language: | English |
| Published: |
2024
|
| In: |
Crime & delinquency
Year: 2024, Volume: 70, Issue: 8, Pages: 1943-1970 |
| Online Access: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Drawer...
|
| Check availability: | HBZ Gateway |
| Keywords: |
MARC
| LEADER | 00000caa a22000002 4500 | ||
|---|---|---|---|
| 001 | 1891320947 | ||
| 003 | DE-627 | ||
| 005 | 20240616025552.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240615s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1177/00111287221106946 |2 doi | |
| 035 | |a (DE-627)1891320947 | ||
| 035 | |a (DE-599)KXP1891320947 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 084 | |a 2,1 |2 ssgn | ||
| 100 | 1 | |a Wo, James C. |e VerfasserIn |0 (DE-588)1153165546 |0 (DE-627)1014587611 |0 (DE-576)499922549 |4 aut | |
| 109 | |a Wo, James C. | ||
| 245 | 1 | 0 | |a Recreating Human Mobility Patterns Through the Lens of Social Media: Using Twitter to Model the Social Ecology of Crime |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Studies of neighborhood crime are often limited in their ability to account for the dynamic nature of human mobility, a central tenet of prominent theoretical perspectives on the spatial distribution of crime. Yet, recent work indicates the utility of social media data for estimating the size and composition of such ambient population. In the present study, we assess whether four Twitter-derived measures are associated with crime counts across 2,348 block groups. Specifically, we focus on the density of Twitter users (and tweets), as well as the proportion of Twitter users (and tweets) that are “insiders.” We inferred Twitter users’ “insider” location from the block group in which they tweeted most frequently. | ||
| 650 | 4 | |a Guardianship | |
| 650 | 4 | |a ambient population | |
| 650 | 4 | |a Social Media | |
| 650 | 4 | |a Routine Activities | |
| 650 | 4 | |a Neighborhood crime | |
| 700 | 1 | |a Rogers, Ethan M. |e VerfasserIn |0 (DE-588)1200444922 |0 (DE-627)1683550749 |4 aut | |
| 700 | 1 | |a Berg, Mark T. |e VerfasserIn |0 (DE-588)1124626344 |0 (DE-627)878865586 |0 (DE-576)340288124 |4 aut | |
| 700 | 1 | |a Koylu, Caglar |e VerfasserIn |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Crime & delinquency |d Thousand Oaks, Calif. [u.a.] : Sage Publications, 1960 |g 70(2024), 8, Seite 1943-1970 |h Online-Ressource |w (DE-627)306655128 |w (DE-600)1499997-3 |w (DE-576)081985045 |x 1552-387X |7 nnns |
| 773 | 1 | 8 | |g volume:70 |g year:2024 |g number:8 |g pages:1943-1970 |
| 856 | 4 | 0 | |u https://doi.org/10.1177/00111287221106946 |x Resolving-System |z lizenzpflichtig |3 Volltext |
| 912 | |a NOMM | ||
| 935 | |a mkri | ||
| 951 | |a AR | ||
| ELC | |a 1 | ||
| LOK | |0 000 xxxxxcx a22 zn 4500 | ||
| LOK | |0 001 453919142X | ||
| LOK | |0 003 DE-627 | ||
| LOK | |0 004 1891320947 | ||
| LOK | |0 005 20240615043604 | ||
| LOK | |0 008 240615||||||||||||||||ger||||||| | ||
| LOK | |0 035 |a (DE-2619)KrimDok#2024-06-14#69D220AA27D9FF1D7FA174CECF17E9CCCE09873A | ||
| LOK | |0 040 |a DE-2619 |c DE-627 |d DE-2619 | ||
| LOK | |0 092 |o n | ||
| LOK | |0 852 |a DE-2619 | ||
| LOK | |0 852 1 |9 00 | ||
| LOK | |0 935 |a zota |a tiep | ||
| ORI | |a WA-MARC-krimdoka001.raw | ||