Abstract
This paper describes several steps towards the development of an online agent (or socialbot) that provides emotional support to stressed users. In particular, we present an empirical study that was conducted with the aim to investigate how people help each other to cope with stressful situations via online social networks. To this end, around 10.000 tweets about stressful situations were collected. Then, using crowdsourcing, these tweets were classified into stress categories, and supportive replies to them were collected, which were also classified into categories. Contingency tables were constructed in order to explore which types of support were most frequently used in which circumstances. The resulting values can be used as parameters for a previously developed algorithm that automatically constructs support messages. This allows our agent to generate supportive messages that are more similar to the support messages that human beings send via social media.
| Original language | English |
|---|---|
| Title of host publication | Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity |
| Subtitle of host publication | The PAAMS Collection - International Workshops of PAAMS 2018, Proceedings |
| Publisher | Springer/Verlag |
| Pages | 196-209 |
| Number of pages | 14 |
| ISBN (Electronic) | 9783319947792 |
| ISBN (Print) | 9783319947785 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | 16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018 - Toledo, Spain Duration: 20 Jun 2018 → 22 Jun 2018 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 887 |
| ISSN (Print) | 1865-0929 |
Conference
| Conference | 16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018 |
|---|---|
| Country | Spain |
| City | Toledo |
| Period | 20/06/18 → 22/06/18 |
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Using crowdsourcing for the development of online emotional support agents. / Medeiros, Lenin; Bosse, Tibor.
Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - International Workshops of PAAMS 2018, Proceedings. Springer/Verlag, 2018. p. 196-209 (Communications in Computer and Information Science; Vol. 887).Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Using crowdsourcing for the development of online emotional support agents
AU - Medeiros, Lenin
AU - Bosse, Tibor
PY - 2018
Y1 - 2018
N2 - This paper describes several steps towards the development of an online agent (or socialbot) that provides emotional support to stressed users. In particular, we present an empirical study that was conducted with the aim to investigate how people help each other to cope with stressful situations via online social networks. To this end, around 10.000 tweets about stressful situations were collected. Then, using crowdsourcing, these tweets were classified into stress categories, and supportive replies to them were collected, which were also classified into categories. Contingency tables were constructed in order to explore which types of support were most frequently used in which circumstances. The resulting values can be used as parameters for a previously developed algorithm that automatically constructs support messages. This allows our agent to generate supportive messages that are more similar to the support messages that human beings send via social media.
AB - This paper describes several steps towards the development of an online agent (or socialbot) that provides emotional support to stressed users. In particular, we present an empirical study that was conducted with the aim to investigate how people help each other to cope with stressful situations via online social networks. To this end, around 10.000 tweets about stressful situations were collected. Then, using crowdsourcing, these tweets were classified into stress categories, and supportive replies to them were collected, which were also classified into categories. Contingency tables were constructed in order to explore which types of support were most frequently used in which circumstances. The resulting values can be used as parameters for a previously developed algorithm that automatically constructs support messages. This allows our agent to generate supportive messages that are more similar to the support messages that human beings send via social media.
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UR - http://www.scopus.com/inward/citedby.url?scp=85049379312&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-94779-2_18
DO - 10.1007/978-3-319-94779-2_18
M3 - Conference contribution
SN - 9783319947785
T3 - Communications in Computer and Information Science
SP - 196
EP - 209
BT - Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity
PB - Springer/Verlag
ER -