Introduction
Related work
Evaluation of individual well-being
Mapping social networks
Evaluation of population well-being
Infectious disease
Mental health
Behavioral health analytics
Work | Social granularity | Measure stress | Type of network data |
---|---|---|---|
Putnam | Communities | Survey | None |
Lin | Individual, organization and communities | Surveys | Community |
Kalimeri | Communities | Surveys | Sociometric badges and bluetooth |
Burt | Communities | Surveys | Interview |
Granovetter | Both on individuals and social groups | Surveys | Interview |
Ciman | Group | Smart phone interactions | Human–smart phone interaction data |
Dillon | Group | Smart phone games | Biofeedback |
Gimpel | Group | Hardware, software sensors and surveys | Sensors |
Anmol Madan | Group | Sensors and surveys | Smart phone sensors and socio-metric surveys |
Amir | Group | Surveys and wearable devices | Sensors and wearable chest belts |
Akane Sano | Group | Surveys and wearable devices | SMS, sensors and surveys |
This work | Individual | Surveys | Call logs |
Social network analysis
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Degree: It is defined as the number of actors (alters) that an ego is directly connected to.
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Farness: It is an aggregate of the weights of the shortest paths from ego/to ego to/from all other nodes. If the social network is directed, then farness can be computed for sending and receiving information from alters, and the sum of geodesic distances from alters is called in-Farness and to other alters is called out-Farness.
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Closeness centrality: It is the reciprocal of farness. This metric is based on the notion of the average shortest path between a node and all the nodes in the graph. It is defined as the mean geodesic distance between an actor and all alters reachable from it. Closeness is an important measure which tells how long it will take information to spread from a given node to other nodes in the network. For a directed graph, in-closeness and out-closeness is calculated separately.
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Structural holes: These are the gaps/weaker connections between non redundant contacts or groups in the social structure. Individuals on either side of a structural hole circulate different flow of information. Structural holes are an opportunity to the broker to pass the information between people from opposite sides of the hole [39].
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Ego betweenness: It is the sum of ego’s proportion of times that ego lies on the shortest path between each part of alters. If the alters are connected to each other not through ego, then the contribution of that pair is 0, for alters connected to each other only through ego, the contribution is 1. Similarly, alters which are linked to ego and one or more other alters, make the contribution 1/n, where n is the total number of nodes connecting the pair of those alters. N Ego Betweenness is normalized by a function of the number of nodes in the ego network [40].
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Proximal betweenness: It measures the number of times a node occurs in a penultimate position on a geodesic. Let ajk be the proportion of all geodesics linking vertex j and vertex k passing through vertex i, where i is the penultimate node on the geodesic, that is (i, k) is the last edge of the geodesic path. The proximal betweenness of a node i is the sum of all ajk where i, j and k are distinct.
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Betweenness centrality: It measures the position of a node and is defined as the number of times a node connects pairs of other nodes who otherwise would not be able to reach one another and plays the role of intermediary in the interaction between the other nodes.
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Flow betweenness: Let ajk be the amount of flow between node j and node k which must pass through i for any maximum flow. The flow betweenness of node i is the sum of all ajk where i, j and k are distinct and j < k. The flow betweenness is, therefore, a measure of the contribution of a node to all possible maximum flows.
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Reach centrality: It counts the number of nodes where each node can reach in k or less steps. For k = 1, this is equivalent to degree centrality. For directed networks, it calculates separate measures for out-Reach and in-Reach. In a social network, when we find the key individuals who are positioned well in the network, via them we can reach many people in just a few steps. This measure gives us a natural metric for evaluating each node.
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Density: It is defined as the total number of ties divided by the total number of possible ties. Given a direct graph, G = (V, E), Density is defined as: Density = |E| |V|*(|V| − 1), where |V| is the total number of vertices and |E| is the total number of the edges of the graph.
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Degree centrality: It is defined as the number of direct connections a node has with other actors or alters. A node with a high degree centrality acts as a hub in the network and for a directed network; degree centrality is the sum of in-degree and out-degree. It signifies activity or popularity of that node in the network due to large number of interactions with other nodes.
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Clique: It can be defined as a sub-set of nodes where all probable pairs of nodes are directly linked to each other.
A social analysis of human stress behavior
Source | Destination | Date and time of call | Type of call |
---|---|---|---|
FA10-01-12 | FA10-01-11 | 11/11/2010 0:19 | Incoming |
FA10-01-11 | FA10-01-12 | 11/11/2010 0:19 | Outgoing |
FA10-01-11 | FA10-01-12 | 11/11/2010 0:20 | Outgoing |
FA10-01-12 | FA10-01-11 | 11/11/2010 0:20 | Incoming |
FA10-01-11 | SP10-01-21 | 11/11/2010 0:20 | Outgoing |
SP10-01-21 | FA10-01-11 | 11/11/2010 0:20 | Incoming |
FA10-01-07 | 2013346763 | 11/11/2010 0:47 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:48 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:48 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:49 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:50 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:51 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:52 | Outgoing |
FA10-01-07 | 2013346763 | 11/11/2010 0:53 | Outgoing |
SP10-01-25 | 6173195257 | 11/11/2010 2:50 | Outgoing |
SP10-01-52 | 8883002305 | 11/11/2010 4:42 | Outgoing |
Nodes | Date | Stress |
---|---|---|
FA10-01-16 | 1/13/2011 | 4 |
FA10-01-16 | 1/14/2011 | 4 |
FA10-01-16 | 1/15/2011 | 1 |
SP10-01-08 | 4/20/2011 | 5 |
SP10-01-21 | 3/5/2011 | 4 |
SP10-01-19 | 11/26/2010 | 4 |
SP10-01-21 | 3/7/2011 | 5 |
SP10-01-21 | 3/1/2011 | 4 |
SP10-01-19 | 11/27/2010 | 4 |
FA10-01-27 | 4/17/2011 | 5 |
SP10-01-21 | 3/9/2011 | 4 |
FA10-01-48 | 2/27/2011 | 5 |
SP10-01-13 | 3/6/2011 | 2 |
SP10-01-42 | 2/27/2011 | 7 |
Stochastic Gradient TreeBoost algorithm
Treenet ananlysis of call log dataset
By | Neg. AvgLL | ROC | Misclass | Lift |
---|---|---|---|---|
Measure | 0.65369 | 0.50000 | 0.36047 | 1.00000 |
N Trees | 171 | 1 | 1 | 1 |
Variable | Score |
---|---|
Closeness | 100.00 |
Hierarchy | 93.27 |
Neigenvec | 89.61 |
Density | 80.97 |
Noutdwreach | 72.86 |
TreeNet analysis (%) | RandomForest analysis (%) | |
---|---|---|
Specificity | 92.86 | 83.71 |
Sensitivity/Recall | 75.71 | 70.33 |
Precision | 63.95 | 35.71 |
F1 statistic | 50.00 | 52.75 |
Hypothesis testing
H No | Hypothesis granularity | Hypothesis: description | Pearson correlation p value | Result: significant | Direction |
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H1 | Overall period | People with more closeness centrality will have more stress than people with less closeness centrality | −0.0568 | Yes | Negative |
H2 | Overall period | An individual’s hierarchical position enables him/her to play the role of intermediary between other nodes, hence obtains more opportunities which makes his/her life more stressful | 0.1214 | No | Positive |
H3 | Overall period | The eigenvalue of an individual positions him/her as central nodes in a network and captures more information, hence feels more stressed | −0.0611 | Yes | Negative |
H4 | Overall period | An individual in a denser network will have more potential connections/relationships with other nodes and promote more sharing of resources, hence individuals are more stressed | −0.0957 | Yes | Negative |
H5 | Overall period | An individual who are well positioned in a network and reach to many people in few number steps are more stressful | −0.0542 | Yes | Negative |