The authors define mobile crowd sensing (MCS) as follows: “a collaborative effort from mobile smartphone users to sense and share their data needed to fulfill a given MCS objective (e.g., modeling of urban traffic or wellness index of a community).” The paper focuses on MCS and statistical analysis of effect and impact on users in the sense of anonymity and intimacy.

The anonymization of data has gained great importance in the networked and mobile environment related to data that are stored about people in various systems. Any mobile device user can take part in MCS, and he or she can collect and communicate data about different situations. Users can provide either anonymous or identifiable data. Smartphones are enabled to sense the user’s environmental context such as location, behavior, interaction with the environment, and use of apps on the phone.

The research question is to investigate the influence of intimacy and intimate environments on decisions such as whether certain pieces of data should be shared either anonymously or not and whether to delete data that is suspected to contain identifiable information. A data collection and statistical method is elaborated. University students were recruited as voluntary participants in enough numbers to produce statistically reasonable results. The other factor analyzed was whether Facebook sharing and anonymous server sharing are significantly different, and what the influencing factors are in the sense of variables. The statistical analysis on the gained data is sound; the paper used ANOVA, z-scores, and p-values to assert whether a factor/variable plays a significant role in a user’s decision to share or delete something.

The final result of the paper is that the level of anonymity of data sharing is determined significantly by the type of content and what the relationship is between the content and the effect that is exercised on user privacy and reputation.

The paper will be interesting for researchers of societal relationships, the role of most recent technology, privacy, and data protection in the context of society.