<|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:"Using Social Network Theory for Modeling Human Mobility."
Abstract:"Human mobility modeling plays an essential role in accurately understanding the performance of data forwarding protocols in mobile networks and has been attracting increasing research interest in recent years. People's movement behaviors are strongly affected by their social interactions with each other, which, however, are not sufficiently considered in most existing mobility models. Recent studies in social network theory have provided many theoretical and experimental results, which are useful and powerful for modeling the realistic social dimension of human mobility. In this article we present a novel human mobility model based on heterogeneous centrality and overlapping community structure in social networks. Instead of extracting communities from artificially generated social graphs, our model manages to construct the k-clique overlapping community structure which satisfies the common statistical features observed from distinct real social networks. This approach achieves a good trade-off between complexity and reality. The simulation results of our model exhibit characteristics observed from real human motion traces, especially heterogeneous human mobility popularity, which has significant impact on data forwarding schemes but has never been considered by existing mobility models.."
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 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [6];
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Q4 = [0];
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Q6 = [1].
Using Social Network Theory for Modeling Human Mobility
Human mobility modeling plays an essential role in accurately understanding the performance of data forwarding protocols in mobile networks and has been attracting increasing research interest in recent years. People's movement behaviors are strongly affected by their social interactions with each other, which, however, are not sufficiently considered in most existing mobility models. Recent studies in social network theory have provided many theoretical and experimental results, which are useful and powerful for modeling the realistic social dimension of human mobility. In this article we present a novel human mobility model based on heterogeneous centrality and overlapping community structure in social networks. Instead of extracting communities from artificially generated social graphs, our model manages to construct the k-clique overlapping community structure which satisfies the common statistical features observed from distinct real social networks. This approach achieves a good trade-off between complexity and reality. The simulation results of our model exhibit characteristics observed from real human motion traces, especially heterogeneous human mobility popularity, which has significant impact on data forwarding schemes but has never been considered by existing mobility models.