Kampal Schools

Demo Relaciones Personales - Colegio Demo

Statistics
Networks
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Colegio Demo

Analytics Communities

Selection

Relationship distance

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Networks

Question

Relationship type

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Modifiers

Display

Size

Node color

Edge color

Filters

Gender

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Communities

Click on a community to see more details

All communities in selection

	Community of	Com Rel	Sel Rel	Members

Member	Sel Rel

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Given a group of respondents (All, a Classroom...) and a given relationship question, we build their Network and calculate their community structure.
Each community contains a number of people, and we label it with the name of the highest-ranking person in the community.
The set of identified communities is shown here, with a pie chart indicating the total number of relationships for each community.
A list of the communities is also shown indicating:

Relationships in the Community: Number of weighted relationships of the members of that community with members of the same community. Relationships of a node with someone outside their community are not counted here.
Relationships in the Selection: Number of weighted relationships of the members in the entire analyzed Network, whether or not they belong to their community. Of course this number is greater than or equal to the previous one.
Members: Number of community members.

Finally, by clicking on each community, all the nodes that compose it are shown, and the number of weighted relationships for each one of them.

Analytics

Name	Classroom	Positive IN relationships	Positive OUT relationships	Negative IN relationships	Negative OUT relationships	Centrality	Relevance	Popularity	Unpopularity	Relationships	Trend

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For the selected set we show a statistical and sociological summary of the responses
The fields shown are:

Respondent ID: The data is shown only to users with privileges. Otherwise, an anonymized identifier is displayed.
Classroom: Name of the classroom to which the respondent belongs.
Positive IN relationships (+): Number of positive incoming relationships. It corresponds to the number of friendships received from other people: The (weighted) number of people who claim to be friends with the user in question Each link is weighted as 1 (Good Relationship) or 2 ("Best Relationship"). In short, it represents the number of people who say that this user is their friend.
Positive OUT links (+): Number of positive outgoing links. Each link is weighted as 1 (Good Relationship) or 2 ("Best Relationship"). It is the number of friendships the user claims to have. It is the number of people (weighted) that the user claims to be friends with. It is the answer to the question: How many friends do you have?
Negative IN relationships (-): Negative relationships can be worth -1 (Bad Relationship) or -2 (Very bad relationship). Here the number of incoming enmities is indicated, i.e. the number of people (weighted) who say they have a bad relationship with the user. In short, it is the number of people in the analyzed network who said they have a bad relationship with the user in question.
Negative OUT relationships (-): The number of enmities that the user claims to have is indicated, i.e. the number of people (weighted) with whom the user claims to have a bad relationship.
Centrality: Measure of the cohesive role played by the person in the network. It takes into account the entire structure of the network, all relationships, and essentially measures how important a user is for information to flow through the network. If user A has a high Centrality (1 is the maximum), it means that for information to go from one user to another, it must almost certainly pass through user A.
Relevance: Measure of the person's weight in the Network. It represents how important are the people with whom that person is friends. If there are relevant people in the group of people the user is friends with, the user is relevant.
Popularity: For each user we first consider all the people who claim to be his/her friend (+ IN relationships), we call these people "First Neighbors". We consider at the same time the people who are friends of the "First Neighbors", which we call "Second Neighbors". Popularity is the number of first and second neighbors of a user (without repeating). It represents the degree of social acceptance of the user in the Network; how well he/she is supported by a group with many friends.
Unpopularity: For each user we consider all the people who say they have a bad relationship with him/her (- IN relationships). These are the first negative neighbors. We consider at the same time the people who are friends of the "First Neighbors", who we call "Second Neighbors". Unpopularity is the number of first and second neighbors of a user (without repeating). The difference with Popularity is that now the first neighbors considered are only the negative ones. It represents the overall "social" rejection of the user in the Network, since the more friends his enemies have, the stronger social rejection will exist.
Relationships: The status of the user's relationships in general is indicated. We distinguish whether he/she has any positive relationships (Yes), no positive or negative relationships (No) or only negative relationships (Negative).
Tendencia: Los grafos están construidos con un algoritmo de fuerzas considerando inicialmente solo las relaciones positivas. De este modo grupos de alumnos especialmente amigos se agrupan en zonas próximas. Cuando incluimos las relaciones negativas, aparecen fuerzas repulsivas por ello, modificando la geometría del grafo, haciendo que los alumnos con relaciones negativas se alejen de su entorno de amistades. Este alejamiento depende del balance de relaciones positivas y negativas, de la distribución de dichas relaciones y del conjunto del entorno. Un alumno con muchas relaciones positivas y alguna negativa, no se ve afectado en su posición. Pero un alumno con bastantes relaciones negativas puede verse “expulsado” de su entorno, poniéndolo en riesgo, pues partía de una situación “buena” de inclusión en la Red y podría acabar en una situación mucho peor. En general por tanto esta inclusión de relaciones negativas produce modificaciones en la posición de cada usuario respecto a su grupo de amistades. Este parámetro mide cuánto se aleja un usuario de su grupo de amigos por el hecho de considerar las relaciones negativas. Clasificamos la Tendencia en varios grados que se muestran en el listado.

All of the above data can be downloaded to a PDF or CSV file.

Help

When a Listing question is created on the test (whether it is conditional or not), and its answer type is "Relationships", it means that a student will indicate his or her relationship with other students.
Suppose that we ask students to tell us who are their friends at classroom. The student will mark one or more classmates.
Therefore, we can generate a relationship graph, where each student is represented by a node, and build a relationship from A to B if A indicated that B is a friend. In this way, we have a directed network, with nodes and tipped arrows between them.
Showing several students (for example, a classroom) and every relationship between them, we will obtain a Graph or Complex Network, which will visualize their relationships structure.

Once this Network is built we can apply Complex Network Theory in order to obtain more information. Next, we point out the main aspects of our analysis.

Nodes: Each person who took the test is represented by a node, which is displayed in a given color and size. By clicking on the node its basic information will be shown.
Links: These are relationships between nodes. A link has a Direction from the person who manifests a relationship to the one indicated on it. (If A says to be friends with B, the arrow comes out from A and reaches B). When a question is graded with "Good relationship", "Very good relationship" type of answers, the first relationship will have a weight of 1 and the second will have a weight of 2.That is, each link has a given weight.
Degree: This is the sum of a node's links. The Total Degree (or, simply, Degree) corresponds to the sum of incoming or outcoming links.
- Incoming Degree (In): This is the sum of the value of the Incoming links to a node. To the question "Who are your friends?", the In Degree is the number of people who have stated that they have a "good relationship" with the node in question (weighs 1 each) plus the number of people who claimed a "very good relationship" (weights 2 each); in other words, the In Degree of a person is the number of people (weighted) who consider that they have a good relationship with that person (in this case Friendship).
- Outgoing Degree: It is the sum of the outgoing links of a node. In the case of the question "Who are your friends", the Out degree is the number of people with "good relationship" (Friends) that person affirms he/she has plus twice (weight = 2) the number of people with whom he/she claims to have a "Very good relationship" (Best Friend).
Generally, the In Degree and Out Degree do not have the same value.
Communities: It refers to the concept of "group of people with a more intense internal relationship between them than with the rest". A community is a group of people who, for the relationship under study, maintain a high number of relationships, making it a well-defined subgroup within the whole group.

By default, when the network is drawn, it is as follows:

Node size: Positive In degree of the node. By size we mean the node's "Area".
Node color: Community to which the node belongs.
Link thickness: Proportional to the intensity of the relationship between nodes.
Link Color: Color of the highest degree node in the relationship.

These default values can be changed in "Modifiers".

Negative mode

By default, only positive relationships are considered in a network. However, people can mark negative negative relationships with other people, and thus influence the social network.
When a person A is friends with two people B and C, and B hates C, it is considered that B weakens the friendship between A and C by being friends with A and hating C.
When the negative mode is activated, negative relationships are displayed in the network (always in red) and communities change due to the weakening between nodes, both their position and their members. This change can be visualized through the corresponding button.

Interface

The actions of each interface button are shown below:

Selection: Selects a network from specific classrooms or students.
Network: Switches between the networks belonging to different relationship questions.
Modifiers: Modify node sizes, node colors and relationships, according to certain parameters; and filter by gender.
Help: Displays this help text.
Search bar: Type part of a node name and press ENTER to focus on the node in question, or several if there are several matches.
Analytics: Data table with the information of all the nodes in the graph.
Communities: Panel of communities, with information about the communities and their members, ignoring negative relationships.
Enlarge: Hides the external interface to show the entire network in full screen.
Download: Download a snapshot of the network as it looks at that moment.
Hide positive links: Hides positive links, does not hide negative links.
Negative mode: Activates negative mode, showing negative links.
Animation: Reproduces the animation generated by applying on a positive-only graph the spacing caused by the negative relationships.