# Self-Disclosure to an IoT Conversational Agent: Effects of Space and User Context on Users'
## 2 Theoretical Background and Research Hypotheses
### Information Types for Self-Disclosure to IoT-CAs
#### 2.1.2 Privacy and Self-Disclosure Boundaries in Human-IoT-CA Interaction  
Supported by artificial intelligence, IoT-CAs can help to personalize services. Specifically, users could receive more personalized services when they disclose more information to a conversational agent [13]. [PERSON] et al. [14] showed that it could be beneficial for users and an IoT-CA to \"get to know each other\" before an IoT-CA exhibits proactive behavior. Furthermore, users would believe that the IoT-CA understood them well and had more confidence in the IoT-CA providing a personalized service when they had previously disclosed personal information (e.g., preferences, habits) to it [12]. In addition, users have privacy concerns if they perceive that too much private information is collected by IoT devices [15]. [PERSON] et al. [16] pointed out that privacy concerns had a negative effect on users' intention to use IoT services. Recently, several IoT-CA providers (e.g., Amazon and Google) have begun to allow users to review and delete their history to address their privacy concerns [17; 18].  
Therefore, there might be a privacy-disclosure boundary for users when using IoT-CAs. On one hand, more value can be obtained from the agents when more information is disclosed [13]. On the other hand, IoT users do not want to engage in too much self-disclosure in order to protect their information privacy [19]. The results of an online survey of 508 IoT service users (dealing with issues such as mobile payment and intelligent transportation) showed that the perceived benefits provided by IoT services had more effect on users' intentions to use IoT services, superseding information privacy concerns [20]. However, the \"information types\" constituting the concerns on information privacy were not defined. More specifically, users may have no problem disclosing some types of personal information for personalized service, whereas they may prefer to keep other types of information private to protect their privacy.  
Jourard's Self-Disclosure Questionnaire (JSDQ; developed by [PERSON] and [PERSON] [21]) has been the most widely used instrument for measuring one's capacity for self-disclosure [22; 23]. The JSDQ classifies personal information into six types: attitudes and opinions, tastes and interests, work, money, personality, and body. It also measures the amount of information that individuals disclose about these types of information. [PERSON] and [PERSON] [21] found the levels of self-disclosure of different types of information vary from person to person. Specifically, information about tastes and interests (information about one's interests, e.g., \"my favorite reading matter\" and \"my likes and dislikes in music\") was disclosed the most, and body information (information about one's physical health and appearance, e.g., \"whether or not I have any health problems\" and \"my past record of illness and treatment\") was disclosed the least. The results of a study by [PERSON] et al. [24] support these results. They noted that information about tastes and interests is not intimate and that participants felt comfortable disclosing it, whereas body information is intimate, which made participants uncomfortable disclosing it. In addition, information about tastes and interests is \"high disclosure\" information in interpersonal communication (e.g., online social network users often reveal their tastes and interests in books, music, and movies in their profiles or on their \"wall\" [25]), whereas body information is \"low disclosure\" information (e.g., people do not want to talk about their physical health to others [26; 27]). According to the CASA paradigm, people may apply their self-disclosure preferences during interpersonal self-disclosure in their interactions with IoT-CAs. Thus, we have the following hypothesis:  
**Hypothesis 1.**_Users are most willing to disclose information about their tastes and interests for better service and are least willing to disclose body information when interacting with IoT-CAs._