Computational social science is thought to be developing along two parallel methodological paths。One is based on agent based modeling，ABM)-based social simulation path，Mainly explores the emergence mechanism and unexpected evolution of macro-complex social phenomena；The other one is based on machine learning、Complex network analysis、bet365 casino bonus path focusing on text analysis，Mainly based on the increasing number of electronic trace big data in the past 20 years as analysis data，Analyze the connections and patterns behind social phenomena by developing new methods。Although two paths have been used in the development of research tools in recent years、Talent training、Knowledge production and other aspects have achieved rapid development，But they also encountered their own development bottlenecks。The former is ridiculed as a “toy model” due to lack of sufficient data to calibrate and validate the model；The latter pays more attention to macro-social models and predictions，Ignore the theoretical explanation of phenomena and be criticized as "exquisite mediocrity"。The former limits the expansion of research topics due to the lack of external data，The latter restricts the depth of its research due to insufficient social theoretical explanations。Facing the increasingly complex social phenomena brought about by digital transformation，The integration of the two methods is imperative，There are many possibilities，There are also several challenges。

　Historical bet365 casino bonus and current dilemma

There are two main explanations for the separation of development paths of computational social science。One explanation is that the two appeared at different times。Social simulation experienced from system dynamics、Three main development stages from cellular automata to actor-based modeling (ABM)，Dating back to the 1940s；bet365 casino bonus mainly appeared in the last 20 years，Especially after Razer and others published the "Manifesto of Computational Social Sciences" in "Nature", it developed rapidly。Another explanation is that there are large differences in the research groups using the two methods and the issues they focus on。Social simulation focuses on the emergence mechanism of macro phenomena，Focus on the complex issues brought about by the "micro-macro" connection，Attracted the attention of a large number of sociologists very early。Big data mining pays more attention to the utilization of newly emerging massive trace data、Administrative big data and other resources to conduct research on human behavior，The main goal is to discover the operating patterns of macro-social phenomena and accurately predict them。Due to the availability of big data resources、Multiple reasons such as method reserve and scene application，This field has long been dominated by a large number of computational scientists and physicists，Course in Economics with Computational Social Sciences、Sociology、There have been certain changes due to the rise of traditional social science fields such as psychology。

Social simulation based on ABM focuses on the macro phenomena emerging from the long-term interaction between individuals and the environment and its unintended consequences，By building an “artificial world” that can represent real society，Set individual interaction rules，Simulate macro-social phenomena that emerge based on long-term interactions based on this rule，such as social isolation、Cultural differentiation、Swarm intelligence, etc.。The biggest challenge facing this method is how to confirm that the interaction rule is the only rule for the emergence of macroscopic phenomena。Different from nature，Social phenomena often have multiple mechanisms and multiple causes，Therefore，Simulations of social phenomena increase the difficulty of this challenge。Researchers need to find the most critical and explanatory mechanism in theory and logic to carry out analysis。At the same time，Need to empirically verify the settings of "Artificial World"，Explain the rationality of attributes and interaction rules through bet365 casino bonus，And it is also necessary to compare the simulation results with the real-world development results to illustrate the rationality of the model。Therefore，There is a growing need in the field for empirically tested “high-dimensional reality” models，The high cost of bet365 casino bonus acquisition and the complexity of the research design limit the expansion of such models，Currently in addition to urban planning、In addition to the rapid development of infectious disease transmission and other fields，There is still no large-scale application in other fields。

At the same time，Although the bet365 casino bonus path is in full swing now，Similarly facing the dilemma of insufficient explainability。On the one hand，This path has been marked with commercial applications earlier，Researchers attach great importance to predictability，Even now some people think “relevance is enough”，No causal explanation required”。On the other hand，The trace big data is not the regular data，The valuable information contained is more sparse，It is difficult to conduct explanatory research using traditional hypothesis testing methods。With the deepening of bet365 casino bonus on traditional social science issues，This path also pays increasing attention to interpretability。For example，Various methods such as "combination of big data and small data", "exploratory and confirmatory comprehensive research" and "large-scale experiments based on the Internet" have been proposed。However，The emergence of big data not only heralds the innovation of methods，It also means the transformation of human society，How people connect with each other、The scale of connections and the pattern of social differentiation are undergoing significant changes。Our future will be a digital society with greater complexity，Social phenomena are becoming increasingly complex and discontinuous。And the understanding of these social phenomena，There is a growing need for “vertical causal” explanations that specifically address complexity。

　Integration bet365 casino bonus and its challenges

Facing increasingly complex social phenomena，The integration of the two methods is imperative。Social simulation that lacks external data calibration and bet365 casino bonus that lacks "longitudinal causal" explanation are merging with each other，Be able to compensate for their respective weaknesses。The macro-social patterns and their correlations discovered through rigorous bet365 casino bonus can provide data support for ABM model construction，At the same time, it also points out the direction for discovering new research problems。ABM provides possible explanations for the social patterns and correlations discovered by bet365 casino bonus，Discover the emergence mechanism behind it，Even conduct experimental studies on possible interventions。Actually，In the 2022 Handbook of Sociological Science，Several analytical sociologists have produced excellent summaries of convergence cases in this area。Overall，The ways of integrating the two mainly include the following three。

First，bet365 casino bonus results serve as a single indicator and become the basis for ABM modeling parameter verification。ABM’s model setting is more flexible，The data basis for different parameter settings can be diversified，So bet365 casino bonus results can enter the ABM model in different ways。For example，The analysis results of population registration big data can be used as the basis for setting the basic attributes of actors in ABM，The analysis results of social network big data can be used as the basis for setting the parameters of the relationship network between actors in ABM, etc.。This is a shallower method fusion，bet365 casino bonus assumes a completely supporting role，The challenge is whether bet365 casino bonus can provide unbiased、Accurate、New indicators not available in other survey data。

Secondly，bet365 casino bonus and social simulation play a supporting role，To jointly deepen our understanding of the problem。A typical case comes from Kaiser (Marijn A. Research on social robots carried out by Keijzer, Michael Mas and others。Existing bet365 casino bonus results are displayed，Social robots play a contradictory role in information dissemination: the information disseminated by social robots is very wide，But it can only affect a few people at the same time。Why social robots can only affect a few people，The information it spreads can spread very widely？In response to this paradox，The author established ABM model analysis and discovery based on the classic communication model，Those robots that quickly attract and change the opinions of a large number of people around them，A circle of communication around which homogeneous views are actually established，Also expands the distance between the circle and its surroundings，Thereby preventing the long-distance transmission of information。In this case，The degree of integration of the two methods is obviously deeper，bet365 casino bonus results provide research questions for ABM modeling，There is an inheritance relationship between the two。Of course，This research can further verify whether the simulation results are consistent with the real-world results through bet365 casino bonus。However，The challenge is that the questions raised by bet365 casino bonus require a mature、Widely accepted ABM model to simulate。In fact，Such models are rare，This undoubtedly hinders the expansion of related topics。

　Third，Establishing an ABM model of “high-dimensional reality” based on bet365 casino bonus。This type of research is what we are most looking forward to，Of course it is also the biggest challenge。One of the challenges is the availability of data，We believe that the ideal big data should be all-encompassing complete data，In fact, even such data currently exists，There are also ethical issues of availability。The second challenge is that big data is natural data，May not be suitable for direct research。Therefore，Some cases appear in experimental research on the Internet。For example，A researcher established a music ranking website，In several experimental groups, the initial downloads of songs ranked in different rankings，The control group has no song download ranking。The “Matthew Effect” of the music market was tested through the above experiment，That is, popular songs may not only be related to the quality of the songs，It also depends on whether it is popular with others in the initial stage，It is related to whether the "Matthew Effect" mechanism is activated。Based on this experiment，Arnout van de Rijt established an empirically verified ABM model through experimental data，Further discovery through simulation analysis，In the long run，The social influence process has a self-correcting mechanism，Make the quality of music consistent with its download ranking。The data of this study is completely based on bet365 casino bonus，The two analysis methods have reached complete integration。

(This article is a phased result of the Yunnan Province "Revitalizing Yunnan Talents" Support Plan Young Talent Special Project "New Paths for Research on Ethnic Relations and Influence Mechanisms in the Era of Computational bet365 casino bonus Science")

(Author’s affiliation: School of Ethnology and bet365 casino bonus, Yunnan University)