Rationale. Previous research. Social Network Theory. Main gap 4/13/2011. Main approaches (in offline studies)

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Boots are Made for Walking: The Spatiality of Social Networks in a Pedestrian, Phone-Free Society Patterns of social interaction in regions without: Implications Rationale Annual Meeting of the Association of American Geographers 2011 Petr Matous, Yasuyuki Todo, Dagne Mojo Yadate 1 Transportation infrastructure Communication technologies Mass-media Effective institutions Disease spread prediction Information dissemination Behavioral network interventions 2 Micro Macro Social Network Theory 1. Degree (Valente, Watts) 2. Transitivity (Burt) 3. Spatial extent (Gould) 4. Frequency of interaction vs. distance (Todo) Patterns of social contagion 3 Distance & probability of a tie frequency of interaction Previous research Distance matters but frequent communication across continents common 4 Main approaches (in offline studies) Main gap 1. Whole networks Limited by (geographical) boundaries set by the researchers Long ties omitted 2. Personal networks Limited by the type of chosen name generators Weak ties omitted 5 How much physical distance matters in relation to other factors not examined in less-developed regions without communication and transportation technologies this is unfortunate considering the high relevance of networks in such contexts 6 1

Research questions In an area without transportation and communication infrastructure: (1) Which factors shape overallpersonal networks? (2) What are the relative roles of physical and social distance in frequency of social interaction? Arsi Zone, Tiyo Woreda 18 kebeles Pop: 182 193 Area: 638 km 2 7 Geography Altitudes & climate zones High >2700m Mid 2200-2400m Low < 1800m DATA Representative sample from all climate zones 1. Randomly selected one kebele(300hh) in each climate zone 2. Randomly selected 100HH in each selected kebele (including very remote hard to access HH) GIS Overall network composition and structure first-name method (McCarthy et al 1997) cues to elicit a sample of respondents alters our study randomnames from the area a representative section of respondents networks Prepared by Ryo Takahashi 11 + special types of ties (comparable to other studies) 12 2

Constructing the battery of first-names 1. 78 random names from the HH head list 2. Same number of male and females Continue until 14 positive answers reached 13 14 Number of households Size (degree) of social networks (1) 60 50 40 30 20 10 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of names the respondent knows among the first 14 names 15 TodoY., MojoD., Matous P., and Ryo T. 2010, "Effects of Geography and Social Networks on Diffusion and Adoption of Agricultural Knowledge: Density 0 10 20 30 40 Size (degree) of social networks (2) 1/( # of names to reach 14 positive answers) similar but based on more questions Kernel density estimate Normal density 0 Degree.05.1 netextent 16 Additional information Efficiently obtain basic info about large number inhabitants (N=4,158) 1. Relationship 2. Walking minute distance (location didn t work) 3. Main mode of contact 4. Frequency of contact 5. Length of the relationship 6. Occupation 7. Ethnicity 8. Religion But no identification no attempt to connect 17 Structure 1. Random 14 pairs 2. Would you say that these two know each other? 3. Proportion -> density proxy 4. What type of alters know each other (total N=4,158) A A D C B D B 18 3

Density Density of social networks # of pairs of alters that know each other Added 80 one more question: Do these two people meet 70independently without you? ) Number of households (ceiling effect? 60 50 40 30 20 10 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Number of pairs who know each other among 14 pairs in the respondent's social network TodoY., MojoD., Matous P., and Ryo T. 2010, "Effects of Geography and Social Networks on Diffusion and Adoption of Agricultural Knowledge: 19 Evidence from Rural Ethiopia," paper presented at the 24th Annual Conference of Applied Regional Science Conference, Nagoya University, 2010. Geography of personal networks 20 Walking is a dominant form of contact 98.2% of alters are contacted solely by walking (3,972 ties) Remaining 1.8% of ties included walking + public transport (40 ties) mobile phone call (16 ties) private vehicle (10 ties) landline call (3 ties). Walking time as a measure of physical distance and cost of contact Overestimates, underestimates, rounding Different walking speeds but Estimated time and measured distance R=0.77 Mean 4.8km/hr (Manhattan 4.7km/hr) 21 22 Distribution of ties in space Frequency of contact depends on distance Mean walking minutes 23 24 4

Personality questions e.g. Suppose that the government will give you either 1000 birr one month from now or 2000 birr in one year and one month from now. Which would you prefer? 25 26 Determinants of personal network characteristics (OLS) Degree (size) Education Education Education Age Age Age Sex 5-9 yrs 10-15 yrs 55-59 yrs 60-64 yrs (male=1) 0.30* 0.38* 0.71* 0.85** 0.30* 27 [units Std Dev] 28 Transitivity (density) [Percentage of alters that know each other] Education Age Hood Education Education Age Age Age Age majority 5-9 yrs 10-15 yrs 40-44 yrs 60-64 yrs 65-69 yrs 70-74 yrs -5.491* -11.03*** -12.74* -15.15* -17.96** -15.65* -10.42** Geographical extent of networks (length of ties) Proportion of neighbors of the same ethnicity within 1km radius 29 [log median walking minutes to alters] Remoteness Geocentrality logmean walking minutes to all other households in the kebele 0.55*** 30 5

Multilevel analysis Frequency categories Ties of the same respondent are not independent observations Hierarchical nature of data Tie level variation Individual level variation Respondent-level error Tie-level error Tie characteristics=γ 00 +γ 01 z j +γ 10 x ij +γ 11 z j x ij +U 0j +U 1j x ij +R ij Hierarchically structured random error effects 31 # ties 2500 2000 1500 1000 500 0 Contact at least once in: 11% 1 2 3 4 2 months or more 25% 15 days to 1 month 39% 3 to 14 days 25% 1 or 2 days 32 Standardized residuals -4-2 0 2 4 Error distribution -4-2 0 2 4 Inverse Normal 33 Tie-level variables Estimate Kin dummy 0.11*** Organization member dummy -0.63*** (log) Walking time -0.37*** (log) Walking time squared -0.02*** Farmer dummy 0.13*** Matching on religion 0.18*** Ethnicity Organization member (log) Walking time 0.14*** not significant 34 Individual-level variables Estimates Patience dummy -0.15*** Cross-level interaction variables High-altitude kebele (log) Walking time -0.06** Signify the difference in effect of a tie-level variable for different individuals Random slopes Estimates Organization member 0.08 (log) Walking time 0.012 Farmer dummy 0.10 Farmer dummy random intercept -0.11 Religion & kinship similar effect for everyone 35 36 6

Outcome of the multilevel model with random effects 1. Networks spatially limited Typical alter 15min (1km) walk A few long ties connect with external world 2. Size Education, age, sex 3. Density Education, age, ethnic composition 4. Geographical reach Geographical location 5. Frequency of contact Distance, altitude, kinship, organization membership, religion, occupation, patience Summary 37 38 Socio-physical distance equivalents Impatience and matching on religion important Each of these app. equivalent to decreasing the walking time by one third The most significant (negative) effect is by organizational membership People who live nearby and know each other only through organizations meet less than people who live 7x farther away and do not known each other through orgs Practical implications for behavioral network interventions Information may get to geographical margins of settlements through long ties but behavior less likely Behavior that needs daily interaction to get transferred won t get far Provide training information within small geographical distances (300m) and to each religious group Community-based orgs are the current mantra of international development but perhaps not so useful for behavioral interventions 39 40 Thank you 7