Sight mechanisms

Once some information pieces have been received, users do not pay the same attention to all of them: they just read some of them, who they might be interested in. This mechanism models this: it allows to select which information pieces are observed by the user. We provide the following sight mechanisms in RELISON:

All
All not discarded
All not propagated
All not discarded nor propagated
All recommended
All train
Count
Recommended

All

This mechanism makes users see all the information pieces they have received.

Configuration file

sight:
  name: All

All not discarded

The users read all the received user-generated contents which have not been discarded earlier by the expiration mechanism.

Configuration file

sight:
  name: All not discarded

All not propagated

The users read all the received user-generated contents which have not been propagated earlier by the user.

Configuration file

sight:
  name: All not propagated

All not discarded nor propagated

A combination of the All not discarded and All not propagated mechanisms: a user sees all the information pieces who he has never propagated or discarded in earlier iterations.

Configuration file

sight:
  name: All not propagated nor discarded

All recommended

When this mechanism is used, each user sees all the information pieces coming from recommended users, and which have not previously propagated by the user.

Parameters

orientation: the neighborhood to consider.
- IN: it considers the incoming neighborhood of the target user.
- OUT: it considers the outgoing neighborhood of the target user.
- UND: it considers the all the possible neighbors of the target users (\(\Gamma_{out}(u) \cup \Gamma_{in}(u)\))
- MUTUAL: it considers as neighbors those who share a reciprocal link with the target user (\(\Gamma_{out}(u) \cap \Gamma_{in}(u)\))

Configuration file

sight:
  name: All recommended
  params:
    orientation:
      type: orientation
      value: IN/OUT/UND/MUTUAL

All train

When this mechanism is used, each user sees all the information pieces not coming from recommended users, and which have not previously propagated by the user.

IN: it considers the incoming neighborhood of the target user.

OUT: it considers the outgoing neighborhood of the target user.

UND: it considers the all the possible neighbors of the target users (\(\Gamma_{out}(u) \cup \Gamma_{in}(u)\))

MUTUAL: it considers as neighbors those who share a reciprocal link with the target user (\(\Gamma_{out}(u) \cap \Gamma_{in}(u)\))

Configuration file

sight:
  name: All train
  params:
    orientation:
      type: orientation
      value: IN/OUT/UND/MUTUAL

Count

Each user sees, at most, a pre-determined number of the received information pieces.

Parameters

numSight: the maximum number of pieces each user sees.

Configuration file

sight:
  name: Count
  params:
    nuSight:
      type: int
      value: number_of_pieces

Recommended

This mechanism defines two probabilities: a probability for seeing pieces coming from recommended links and a probability for seeing pieces coming from the rest of the users.

Parameters

probRec: the probability of observing coming from links created via a recommendation
orientation: the neighborhood from which information pieces come. It is used to determine which of the users come from a recommendation and which of them do not.
- IN: it considers the incoming neighborhood of the target user.
- OUT: it considers the outgoing neighborhood of the target user.
- UND: it considers the all the possible neighbors of the target users (\(\Gamma_{out}(u) \cup \Gamma_{in}(u)\))
- MUTUAL: it considers as neighbors those who share a reciprocal link with the target user (\(\Gamma_{out}(u) \cap \Gamma_{in}(u)\))
probTrain: the probability of observing an information piece from the original links in the network.

Note: when used in code, there is another option, which takes as input a graph containing the probabilities. However, this option is not (at the moment) available from a configuration file.

Configuration file

selection:
  name: Recommended
  params:
    probRec:
      type: double
      value: probability
    probTrain:
      type: double
      value: probability
    orientation:
      type: orientation
      value: IN/OUT/UND/MUTUAL