Measurement of Social Capital through Data Mining Techniques at Universidad ECCI

Manuel Fernando Cabrera Jimenez, Olga Camila Hernandez Morales, Luz Stella Garcia Monsalve, Luz Adriana Suarez Suarez


By using Naive Bayes and C4.5 algorithms of data mining, the study of social capital at Universidad ECCI is addressed to identify the community’s potential to generate positive associative relations that impact upon the quality of the citizen the Institution is delivering to the nation. A data collection instrument (survey) was applied that, from the cognitive and structural dimensions, permits characterizing the community’s perception against elements like trust, norms, reciprocity, associativity, and cohesion regarding common objectives. Data were classified to identify the accumulated stock of social capital at the university to promote the generation of networks aimed to benefit the whole community, besides materializing the institutional mission and vision. As a result, the study identified low accumulated stock of social capital at the university; hence, it may be stated – in the first place – that the institution presents low levels of trust in all its participants, which affects construction of associativity strategies so that, from internal relationships, networks may be constructed to be part of the organizational assets; in the second place, the level of recognition and cohesion of the community tends to be at medium levels, a situation that leads to rethinking strategies that accomplish the materialization of the mission and vision in the construction of a much more committed community aware of its internal processes. In the third place, the study permits generating a diagnosis that reveals shortcomings in relation to participation in collegiate entities, where it is fundamental to involve the interests of the members of the community. 


Social capital, Data Mining, Dropo out, ECCI teachers

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