<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Modeling the scaling properties of human mobility in virtual space."
Abstract:"People are increasingly involved in online activities. Online activities can be regarded as movements in virtual space, such as jumping from webpage to webpage while surfing online, switching channels while watching TV, and browsing commodities while shopping online, which can affect information propagation, innovation spread, social activities, etc. Most previous efforts have been devoted to modeling the scaling properties of human mobility in physical space. Few studies aim to establish a unified and integral model to understand the fundamental dynamics underlying human virtual mobility. In this paper, we study human mobility in virtual space empirically and theoretically based on two datasets involving TV watching and online shopping and attempt to answer three unsolved issues. First, human virtual mobility shares common features, supported by the fact that striking agreements appear in the scaling properties of both datasets. Second, there exists a universal rule governing an individual's choice in virtual mobility, which is distinct from that in the real world due to travel restrictions. Third, there exists a unified model incorporating the behavior rule unique to virtual space under the framework of Exploration and Preferential Return, which can be used to reproduce the scaling properties of virtual mobility. We reveal the mechanism behind human virtual mobility through consistent scaling properties and develop a corresponding dynamic model based on empirical data.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
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Q5 = [];
Q6 = [1].
Modeling the scaling properties of human mobility in virtual space
People are increasingly involved in online activities. Online activities can be regarded as movements in virtual space, such as jumping from webpage to webpage while surfing online, switching channels while watching TV, and browsing commodities while shopping online, which can affect information propagation, innovation spread, social activities, etc. Most previous efforts have been devoted to modeling the scaling properties of human mobility in physical space. Few studies aim to establish a unified and integral model to understand the fundamental dynamics underlying human virtual mobility. In this paper, we study human mobility in virtual space empirically and theoretically based on two datasets involving TV watching and online shopping and attempt to answer three unsolved issues. First, human virtual mobility shares common features, supported by the fact that striking agreements appear in the scaling properties of both datasets. Second, there exists a universal rule governing an individual's choice in virtual mobility, which is distinct from that in the real world due to travel restrictions. Third, there exists a unified model incorporating the behavior rule unique to virtual space under the framework of Exploration and Preferential Return, which can be used to reproduce the scaling properties of virtual mobility. We reveal the mechanism behind human virtual mobility through consistent scaling properties and develop a corresponding dynamic model based on empirical data.