<|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:"Spatial mining of migration patterns from web demographics."
Abstract:"Volunteered Geographic Information, social media, and data from Information and Communication Technology are emerging sources of big data that contribute to the development and understanding of the spatiotemporal distribution of human population. However, the inherent anonymity of these crowd-sourced or crowd-harvested data sources lack the socioeconomic and demographic attributes to examine and explain human mobility and spatiotemporal patterns. In this paper, we investigate an Internet-based demographic data source, personal microdata databases publicly accessible on the World Wide Web (hereafter web demographics), as potential sources of aspatial and spatiotemporal information regarding the landscape of human dynamics. The objectives of this paper are twofold: (1) to develop an analytical framework to identify mobile population from web demographics as an individual-level residential history data, and (2) to explore their geographic and demographic patterns of migration. Using web demographics of Vietnamese-Americans in Texas collected in 2010 as a case study, this paper (1) addresses entity resolution and identifies mobile population through the application of a Cost-Sensitive Alternative Decision Tree (CS-ADT) algorithm, (2) investigates migration pathways and clusters to include both short- and long-distance patterns, and (3) analyze the demographic characteristics of mobile population and the functional relationship with travel distance. By linking the physical space at the individual level, this unique methodology attempts to enhance the understanding of human movement at multiple spatial scales.."
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 = [1];
Q2 = [];
Q3 = [];
Q4 = [0];
Q5 = [];
Q6 = [1].
Spatial mining of migration patterns from web demographics
Volunteered Geographic Information, social media, and data from Information and Communication Technology are emerging sources of big data that contribute to the development and understanding of the spatiotemporal distribution of human population. However, the inherent anonymity of these crowd-sourced or crowd-harvested data sources lack the socioeconomic and demographic attributes to examine and explain human mobility and spatiotemporal patterns. In this paper, we investigate an Internet-based demographic data source, personal microdata databases publicly accessible on the World Wide Web (hereafter web demographics), as potential sources of aspatial and spatiotemporal information regarding the landscape of human dynamics. The objectives of this paper are twofold: (1) to develop an analytical framework to identify mobile population from web demographics as an individual-level residential history data, and (2) to explore their geographic and demographic patterns of migration. Using web demographics of Vietnamese-Americans in Texas collected in 2010 as a case study, this paper (1) addresses entity resolution and identifies mobile population through the application of a Cost-Sensitive Alternative Decision Tree (CS-ADT) algorithm, (2) investigates migration pathways and clusters to include both short- and long-distance patterns, and (3) analyze the demographic characteristics of mobile population and the functional relationship with travel distance. By linking the physical space at the individual level, this unique methodology attempts to enhance the understanding of human movement at multiple spatial scales.