|Social media platforms and messenger services such as Telegram have created a new way of publishing and consuming news. To combat the resulting negative effects, such as disinformation, social media analytics (SMA) can be applied to, inter alia, reconstruct the spread of information across platforms or to identify key actors and interactions between users. This paper examines metadata in Telegram to provide a privacy-friendly basis for further SMA. The characteristics of 770 Telegram channels and groups were derived by extracting initial key figures. We observed that messages that were created in channels were forwarded to other actors, while not a single original message created in groups was forwarded. This suggests that channels have a much greater impact on generating and spreading information to other Telegram actors than groups.