TY  - JOUR
A1  - Loh, Frank
A1  - Wamser, Florian
A1  - Poignée, Fabian
A1  - Geißler, Stefan
A1  - Hoßfeld, Tobias
T1  - YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis
JF  - Scientific Data
N2  - Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.
KW  - internet traffic
KW  - mobile streaming
KW  - YouTube
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300240
VL  - 9
IS  - 1
ER  - 
TY  - JOUR
A1  - Carolus, Astrid
A1  - Wienrich, Carolin
A1  - Törke, Anna
A1  - Friedel, Tobias
A1  - Schwietering, Christian
A1  - Sperzel, Mareike
T1  - ‘Alexa, I feel for you!’ Observers’ empathetic reactions towards a conversational agent
JF  - Frontiers in Computer Science
N2  - Conversational agents and smart speakers have grown in popularity offering a variety of options for use, which are available through intuitive speech operation. In contrast to the standard dyad of a single user and a device, voice-controlled operations can be observed by further attendees resulting in new, more social usage scenarios. Referring to the concept of ‘media equation’ and to research on the idea of ‘computers as social actors,’ which describes the potential of technology to trigger emotional reactions in users, this paper asks for the capacity of smart speakers to elicit empathy in observers of interactions. In a 2 × 2 online experiment, 140 participants watched a video of a man talking to an Amazon Echo either rudely or neutrally (factor 1), addressing it as ‘Alexa’ or ‘Computer’ (factor 2). Controlling for participants’ trait empathy, the rude treatment results in participants’ significantly higher ratings of empathy with the device, compared to the neutral treatment. The form of address had no significant effect. Results were independent of the participants’ gender and usage experience indicating a rather universal effect, which confirms the basic idea of the media equation. Implications for users, developers and researchers were discussed in the light of (future) omnipresent voice-based technology interaction scenarios.
KW  - conversational agent
KW  - empathy
KW  - smart speaker
KW  - media equation
KW  - computers as social actors
KW  - human-computer interaction
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-258807
VL  - 3
ER  -