| Item type |
文献 / Documents(1) |
| 公開日 |
2019-07-12 |
| アクセス権 |
|
|
アクセス権 |
open access |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| タイトル |
|
|
タイトル |
Ego-state Estimation from Short Texts Based on Sentence Distributed Representation |
| 著者 |
松本, 和幸
タナカ, サトシ
吉田, 稔
北, 研二
任, 福継
|
| 抄録 |
|
|
内容記述 |
Human personality multilaterally consists of complex elements. Egogram is a method to classify personalities into patterns according to combinations of five levels of ego-states. With the recent development of Social Networking Services (SNS), a number of studies have attempted to judge personality from statements appearing on various social networking sites. However, there are several problems associated with personality judgment based on the superficial information found in such statements. For example, one's personality is not always reflected in every statement that one makes, and statements are influenced by a personality that tends to change over time. It is also important to collect sufficient amounts of statement data including the results of personality judgments. In this paper, to produce an automatic egogram judgment, we focused on the short texts found on certain SNS sites, especially microblogs. We represented Twitter user comments with a distributed representation (sentence vector) in pre-training and then sought to create a model to estimate the ego-state levels of each Twitter user using a deep neural network. Experimental results showed that our proposed method estimated ego-states with higher accuracy than the baseline method based on bag of words. To investigate changes of personality over time, we analyzed how the match rates of the estimation results changed before/after the egogram judgment. Moreover, we confirmed that the personality pattern classification was improved by adding a feature expressing the degree of formality of the sentence. |
| キーワード |
|
|
主題 |
Egogram |
| キーワード |
|
|
主題 |
Personality Estimation |
| キーワード |
|
|
主題 |
Twitter |
| キーワード |
|
|
主題 |
Social Networking Service |
| キーワード |
|
|
主題 |
Distributed Representation |
| キーワード |
|
|
主題 |
Deep Neural Network |
| 書誌情報 |
en : International Journal of Advanced Intelligence
巻 9,
号 2,
p. 145-161,
発行日 2017-05
|
| 収録物ID |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
18833918 |
| 出版者 |
|
|
出版者 |
AIA International Advanced Information Institute |
| EID |
|
|
識別子 |
324505 |
| 言語 |
|
|
言語 |
eng |
ijai_9_2_145.pdf (1.09 MB)
