Fusing Social Media Cues: Personality Prediction from Twitter and Instagram

被引：71

作者：

Skowron, Marcin ^{[1
]}

Tkallcic, Marko ^{[2
]}

Ferwerda, Bruce ^{[3
]}

Schedl, Markus ^{[3
]}

机构：

[1] Johannes Kepler Univ Linz, OFAI, Linz, Austria

[2] Free Univ Bolzano, Bolzano, Italy

[3] Johannes Kepler Univ Linz, Linz, Austria

来源：

PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'16 COMPANION) | 2016年

基金：

奥地利科学基金会;

关键词：

social media mining; user modelling; personality computing;

D O I：

10.1145/2872518.2889368

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Incorporating users' personality traits has shown to be instrumental in many personalized retrieval and recommender systems. Analysis of users' digital traces has become an important resource for inferring personality traits. To date, the analysis of users' explicit and latent characteristics is typically restricted to a single social networking site (SNS). In this work, we propose a novel method that integrates text, image, and users' meta features from two different SNSs: Twitter and Instagram. Our preliminary results indicate that the joint analysis of users' simultaneous activities in two popular SNSs seems to lead to a consistent decrease of the prediction errors for each personality trait.

引用

页码：107 / 108

页数：2

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